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    "# Riskfolio-Lib Tutorial: \n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 2: Portfolio Optimization with Risk Factors using Stepwise Regression\n",
    "\n",
    "## 1. Downloading the data:"
   ]
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    {
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     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  30 of 30 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "\n",
    "assets.sort()\n",
    "\n",
    "# Tickers of factors\n",
    "\n",
    "factors = ['MTUM', 'QUAL', 'VLUE', 'SIZE', 'USMV']\n",
    "factors.sort()\n",
    "\n",
    "tickers = assets + factors\n",
    "tickers.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(tickers, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = tickers"
   ]
  },
  {
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   "execution_count": 2,
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MTUM</th>\n",
       "      <th>QUAL</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>USMV</th>\n",
       "      <th>VLUE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>0.4735%</td>\n",
       "      <td>0.2672%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.6780%</td>\n",
       "      <td>0.1634%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-0.5267%</td>\n",
       "      <td>-1.1914%</td>\n",
       "      <td>-0.5380%</td>\n",
       "      <td>-0.6253%</td>\n",
       "      <td>-1.8277%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-2.2293%</td>\n",
       "      <td>-2.3798%</td>\n",
       "      <td>-1.7181%</td>\n",
       "      <td>-1.6215%</td>\n",
       "      <td>-2.1609%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>-0.9548%</td>\n",
       "      <td>-1.1377%</td>\n",
       "      <td>-1.1978%</td>\n",
       "      <td>-1.0086%</td>\n",
       "      <td>-1.0873%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>0.6043%</td>\n",
       "      <td>0.1480%</td>\n",
       "      <td>-0.5898%</td>\n",
       "      <td>0.1491%</td>\n",
       "      <td>-0.6184%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "               MTUM     QUAL     SIZE     USMV     VLUE\n",
       "Date                                                   \n",
       "2016-01-05  0.4735%  0.2672%  0.0000%  0.6780%  0.1634%\n",
       "2016-01-06 -0.5267% -1.1914% -0.5380% -0.6253% -1.8277%\n",
       "2016-01-07 -2.2293% -2.3798% -1.7181% -1.6215% -2.1609%\n",
       "2016-01-08 -0.9548% -1.1377% -1.1978% -1.0086% -1.0873%\n",
       "2016-01-11  0.6043%  0.1480% -0.5898%  0.1491% -0.6184%"
      ]
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   "source": [
    "# Calculating returns\n",
    "\n",
    "X = data[factors].pct_change().dropna()\n",
    "Y = data[assets].pct_change().dropna()\n",
    "\n",
    "display(X.head())"
   ]
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    "## 2. Estimating Mean Variance Portfolios\n",
    "\n",
    "### 2.1 Estimating the loadings matrix.\n",
    "\n",
    "This part is just to visualize how Riskfolio-Lib calculates a loadings matrix."
   ]
  },
  {
   "cell_type": "code",
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       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_76e2e_level0_col0\" class=\"col_heading level0 col0\" >const</th>\n",
       "      <th id=\"T_76e2e_level0_col1\" class=\"col_heading level0 col1\" >MTUM</th>\n",
       "      <th id=\"T_76e2e_level0_col2\" class=\"col_heading level0 col2\" >QUAL</th>\n",
       "      <th id=\"T_76e2e_level0_col3\" class=\"col_heading level0 col3\" >SIZE</th>\n",
       "      <th id=\"T_76e2e_level0_col4\" class=\"col_heading level0 col4\" >USMV</th>\n",
       "      <th id=\"T_76e2e_level0_col5\" class=\"col_heading level0 col5\" >VLUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_76e2e_row0_col0\" class=\"data row0 col0\" >-0.0006</td>\n",
       "      <td id=\"T_76e2e_row0_col1\" class=\"data row0 col1\" >-0.6551</td>\n",
       "      <td id=\"T_76e2e_row0_col2\" class=\"data row0 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row0_col3\" class=\"data row0 col3\" >0.9406</td>\n",
       "      <td id=\"T_76e2e_row0_col4\" class=\"data row0 col4\" >-0.7883</td>\n",
       "      <td id=\"T_76e2e_row0_col5\" class=\"data row0 col5\" >1.7237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_76e2e_row1_col0\" class=\"data row1 col0\" >0.0005</td>\n",
       "      <td id=\"T_76e2e_row1_col1\" class=\"data row1 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row1_col2\" class=\"data row1 col2\" >1.1744</td>\n",
       "      <td id=\"T_76e2e_row1_col3\" class=\"data row1 col3\" >0.3616</td>\n",
       "      <td id=\"T_76e2e_row1_col4\" class=\"data row1 col4\" >-0.4322</td>\n",
       "      <td id=\"T_76e2e_row1_col5\" class=\"data row1 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_76e2e_row2_col0\" class=\"data row2 col0\" >0.0003</td>\n",
       "      <td id=\"T_76e2e_row2_col1\" class=\"data row2 col1\" >0.3146</td>\n",
       "      <td id=\"T_76e2e_row2_col2\" class=\"data row2 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row2_col3\" class=\"data row2 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row2_col4\" class=\"data row2 col4\" >0.7717</td>\n",
       "      <td id=\"T_76e2e_row2_col5\" class=\"data row2 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_76e2e_row3_col0\" class=\"data row3 col0\" >-0.0003</td>\n",
       "      <td id=\"T_76e2e_row3_col1\" class=\"data row3 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row3_col2\" class=\"data row3 col2\" >0.8123</td>\n",
       "      <td id=\"T_76e2e_row3_col3\" class=\"data row3 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row3_col4\" class=\"data row3 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row3_col5\" class=\"data row3 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_76e2e_row4_col0\" class=\"data row4 col0\" >0.0001</td>\n",
       "      <td id=\"T_76e2e_row4_col1\" class=\"data row4 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row4_col2\" class=\"data row4 col2\" >0.4958</td>\n",
       "      <td id=\"T_76e2e_row4_col3\" class=\"data row4 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row4_col4\" class=\"data row4 col4\" >0.4962</td>\n",
       "      <td id=\"T_76e2e_row4_col5\" class=\"data row4 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_76e2e_row5_col0\" class=\"data row5 col0\" >0.0001</td>\n",
       "      <td id=\"T_76e2e_row5_col1\" class=\"data row5 col1\" >-0.5595</td>\n",
       "      <td id=\"T_76e2e_row5_col2\" class=\"data row5 col2\" >-0.2157</td>\n",
       "      <td id=\"T_76e2e_row5_col3\" class=\"data row5 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row5_col4\" class=\"data row5 col4\" >1.8341</td>\n",
       "      <td id=\"T_76e2e_row5_col5\" class=\"data row5 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_76e2e_row6_col0\" class=\"data row6 col0\" >-0.0003</td>\n",
       "      <td id=\"T_76e2e_row6_col1\" class=\"data row6 col1\" >-0.4782</td>\n",
       "      <td id=\"T_76e2e_row6_col2\" class=\"data row6 col2\" >-0.5993</td>\n",
       "      <td id=\"T_76e2e_row6_col3\" class=\"data row6 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row6_col4\" class=\"data row6 col4\" >2.0793</td>\n",
       "      <td id=\"T_76e2e_row6_col5\" class=\"data row6 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_76e2e_row7_col0\" class=\"data row7 col0\" >0.0004</td>\n",
       "      <td id=\"T_76e2e_row7_col1\" class=\"data row7 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row7_col2\" class=\"data row7 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row7_col3\" class=\"data row7 col3\" >0.3631</td>\n",
       "      <td id=\"T_76e2e_row7_col4\" class=\"data row7 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row7_col5\" class=\"data row7 col5\" >0.8090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_76e2e_row8_col0\" class=\"data row8 col0\" >0.0002</td>\n",
       "      <td id=\"T_76e2e_row8_col1\" class=\"data row8 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row8_col2\" class=\"data row8 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row8_col3\" class=\"data row8 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row8_col4\" class=\"data row8 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row8_col5\" class=\"data row8 col5\" >1.2514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_76e2e_row9_col0\" class=\"data row9 col0\" >0.0001</td>\n",
       "      <td id=\"T_76e2e_row9_col1\" class=\"data row9 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row9_col2\" class=\"data row9 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row9_col3\" class=\"data row9 col3\" >0.3412</td>\n",
       "      <td id=\"T_76e2e_row9_col4\" class=\"data row9 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row9_col5\" class=\"data row9 col5\" >0.5797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_76e2e_row10_col0\" class=\"data row10 col0\" >0.0005</td>\n",
       "      <td id=\"T_76e2e_row10_col1\" class=\"data row10 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row10_col2\" class=\"data row10 col2\" >0.3077</td>\n",
       "      <td id=\"T_76e2e_row10_col3\" class=\"data row10 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row10_col4\" class=\"data row10 col4\" >-0.5485</td>\n",
       "      <td id=\"T_76e2e_row10_col5\" class=\"data row10 col5\" >1.1512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_76e2e_row11_col0\" class=\"data row11 col0\" >-0.0001</td>\n",
       "      <td id=\"T_76e2e_row11_col1\" class=\"data row11 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row11_col2\" class=\"data row11 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row11_col3\" class=\"data row11 col3\" >0.3642</td>\n",
       "      <td id=\"T_76e2e_row11_col4\" class=\"data row11 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row11_col5\" class=\"data row11 col5\" >0.6767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_76e2e_row12_col0\" class=\"data row12 col0\" >0.0003</td>\n",
       "      <td id=\"T_76e2e_row12_col1\" class=\"data row12 col1\" >-0.2693</td>\n",
       "      <td id=\"T_76e2e_row12_col2\" class=\"data row12 col2\" >0.6808</td>\n",
       "      <td id=\"T_76e2e_row12_col3\" class=\"data row12 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row12_col4\" class=\"data row12 col4\" >0.6066</td>\n",
       "      <td id=\"T_76e2e_row12_col5\" class=\"data row12 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_76e2e_row13_col0\" class=\"data row13 col0\" >-0.0004</td>\n",
       "      <td id=\"T_76e2e_row13_col1\" class=\"data row13 col1\" >-0.4572</td>\n",
       "      <td id=\"T_76e2e_row13_col2\" class=\"data row13 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row13_col3\" class=\"data row13 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row13_col4\" class=\"data row13 col4\" >1.4359</td>\n",
       "      <td id=\"T_76e2e_row13_col5\" class=\"data row13 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_76e2e_row14_col0\" class=\"data row14 col0\" >0.0005</td>\n",
       "      <td id=\"T_76e2e_row14_col1\" class=\"data row14 col1\" >1.0302</td>\n",
       "      <td id=\"T_76e2e_row14_col2\" class=\"data row14 col2\" >0.6530</td>\n",
       "      <td id=\"T_76e2e_row14_col3\" class=\"data row14 col3\" >-0.2640</td>\n",
       "      <td id=\"T_76e2e_row14_col4\" class=\"data row14 col4\" >-0.2595</td>\n",
       "      <td id=\"T_76e2e_row14_col5\" class=\"data row14 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_76e2e_row15_col0\" class=\"data row15 col0\" >-0.0000</td>\n",
       "      <td id=\"T_76e2e_row15_col1\" class=\"data row15 col1\" >-0.4648</td>\n",
       "      <td id=\"T_76e2e_row15_col2\" class=\"data row15 col2\" >-0.4612</td>\n",
       "      <td id=\"T_76e2e_row15_col3\" class=\"data row15 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row15_col4\" class=\"data row15 col4\" >2.3257</td>\n",
       "      <td id=\"T_76e2e_row15_col5\" class=\"data row15 col5\" >-0.3532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_76e2e_row16_col0\" class=\"data row16 col0\" >0.0003</td>\n",
       "      <td id=\"T_76e2e_row16_col1\" class=\"data row16 col1\" >-0.4420</td>\n",
       "      <td id=\"T_76e2e_row16_col2\" class=\"data row16 col2\" >1.0319</td>\n",
       "      <td id=\"T_76e2e_row16_col3\" class=\"data row16 col3\" >0.2217</td>\n",
       "      <td id=\"T_76e2e_row16_col4\" class=\"data row16 col4\" >-0.4831</td>\n",
       "      <td id=\"T_76e2e_row16_col5\" class=\"data row16 col5\" >0.7536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_76e2e_row17_col0\" class=\"data row17 col0\" >-0.0004</td>\n",
       "      <td id=\"T_76e2e_row17_col1\" class=\"data row17 col1\" >-0.3311</td>\n",
       "      <td id=\"T_76e2e_row17_col2\" class=\"data row17 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row17_col3\" class=\"data row17 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row17_col4\" class=\"data row17 col4\" >1.7073</td>\n",
       "      <td id=\"T_76e2e_row17_col5\" class=\"data row17 col5\" >-0.4915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_76e2e_row18_col0\" class=\"data row18 col0\" >-0.0005</td>\n",
       "      <td id=\"T_76e2e_row18_col1\" class=\"data row18 col1\" >-0.3267</td>\n",
       "      <td id=\"T_76e2e_row18_col2\" class=\"data row18 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row18_col3\" class=\"data row18 col3\" >0.2594</td>\n",
       "      <td id=\"T_76e2e_row18_col4\" class=\"data row18 col4\" >0.6973</td>\n",
       "      <td id=\"T_76e2e_row18_col5\" class=\"data row18 col5\" >0.4801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_76e2e_row19_col0\" class=\"data row19 col0\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row19_col1\" class=\"data row19 col1\" >-0.4414</td>\n",
       "      <td id=\"T_76e2e_row19_col2\" class=\"data row19 col2\" >-0.3693</td>\n",
       "      <td id=\"T_76e2e_row19_col3\" class=\"data row19 col3\" >-0.2898</td>\n",
       "      <td id=\"T_76e2e_row19_col4\" class=\"data row19 col4\" >1.2928</td>\n",
       "      <td id=\"T_76e2e_row19_col5\" class=\"data row19 col5\" >0.7562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_76e2e_row20_col0\" class=\"data row20 col0\" >0.0005</td>\n",
       "      <td id=\"T_76e2e_row20_col1\" class=\"data row20 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row20_col2\" class=\"data row20 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row20_col3\" class=\"data row20 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row20_col4\" class=\"data row20 col4\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row20_col5\" class=\"data row20 col5\" >0.7562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_76e2e_row21_col0\" class=\"data row21 col0\" >0.0002</td>\n",
       "      <td id=\"T_76e2e_row21_col1\" class=\"data row21 col1\" >0.2867</td>\n",
       "      <td id=\"T_76e2e_row21_col2\" class=\"data row21 col2\" >0.5400</td>\n",
       "      <td id=\"T_76e2e_row21_col3\" class=\"data row21 col3\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row21_col4\" class=\"data row21 col4\" >0.3864</td>\n",
       "      <td id=\"T_76e2e_row21_col5\" class=\"data row21 col5\" >0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_76e2e_row22_col0\" class=\"data row22 col0\" >-0.0003</td>\n",
       "      <td id=\"T_76e2e_row22_col1\" class=\"data row22 col1\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row22_col2\" class=\"data row22 col2\" >0.4485</td>\n",
       "      <td id=\"T_76e2e_row22_col3\" class=\"data row22 col3\" >0.4429</td>\n",
       "      <td id=\"T_76e2e_row22_col4\" class=\"data row22 col4\" >-0.6363</td>\n",
       "      <td id=\"T_76e2e_row22_col5\" class=\"data row22 col5\" >0.8108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_76e2e_row23_col0\" class=\"data row23 col0\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row23_col1\" class=\"data row23 col1\" >-0.5099</td>\n",
       "      <td id=\"T_76e2e_row23_col2\" class=\"data row23 col2\" >-0.5271</td>\n",
       "      <td id=\"T_76e2e_row23_col3\" class=\"data row23 col3\" >-0.2886</td>\n",
       "      <td id=\"T_76e2e_row23_col4\" class=\"data row23 col4\" >1.8941</td>\n",
       "      <td id=\"T_76e2e_row23_col5\" class=\"data row23 col5\" >0.4321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76e2e_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_76e2e_row24_col0\" class=\"data row24 col0\" >0.0004</td>\n",
       "      <td id=\"T_76e2e_row24_col1\" class=\"data row24 col1\" >-0.2371</td>\n",
       "      <td id=\"T_76e2e_row24_col2\" class=\"data row24 col2\" >0.0000</td>\n",
       "      <td id=\"T_76e2e_row24_col3\" class=\"data row24 col3\" >0.3553</td>\n",
       "      <td id=\"T_76e2e_row24_col4\" class=\"data row24 col4\" >-0.8203</td>\n",
       "      <td id=\"T_76e2e_row24_col5\" class=\"data row24 col5\" >1.6431</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x17db50990>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import riskfolio as rp\n",
    "\n",
    "step = 'Forward' # Could be Forward or Backward stepwise regression\n",
    "loadings = rp.loadings_matrix(X=X, Y=Y, stepwise=step)\n",
    "\n",
    "loadings.style.format(\"{:.4f}\").background_gradient(cmap='RdYlGn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.9508%</td>\n",
       "      <td>11.8687%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.7091%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.3627%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.4798%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.5106%</td>\n",
       "      <td>1.3028%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.0984%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 5.9508% 11.8687% 0.0000% 0.0000% 9.7091% 0.0000% 4.3627%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.4798% 0.0000% 0.0000% 0.0000% 0.0000% 5.5106%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 1.3028% 0.0000% 4.0984% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Building the portfolio object\n",
    "port = rp.Portfolio(returns=Y)\n",
    "\n",
    "# Calculating optimal portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov)\n",
    "\n",
    "port.factors = X\n",
    "port.factors_stats(method_mu=method_mu, method_cov=method_cov)\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "port.alpha = 0.05\n",
    "model='FM' # Factor Model\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = False # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the composition of the portfolio\n",
    "\n",
    "ax = rp.plot_pie(w=w, title='Sharpe FM Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                 height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9932%</td>\n",
       "      <td>4.4200%</td>\n",
       "      <td>3.5980%</td>\n",
       "      <td>8.4944%</td>\n",
       "      <td>5.0090%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.4334%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0935%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>13.3194%</td>\n",
       "      <td>1.0113%</td>\n",
       "      <td>8.3006%</td>\n",
       "      <td>4.0840%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3126%</td>\n",
       "      <td>1.6683%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6594%</td>\n",
       "      <td>6.2598%</td>\n",
       "      <td>1.2539%</td>\n",
       "      <td>3.4249%</td>\n",
       "      <td>10.4169%</td>\n",
       "      <td>3.1169%</td>\n",
       "      <td>0.3979%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.5871%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.7064%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.7371%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.7064%</td>\n",
       "      <td>4.9334%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5790%</td>\n",
       "      <td>1.6514%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.3023%</td>\n",
       "      <td>7.3159%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.0349%</td>\n",
       "      <td>11.1003%</td>\n",
       "      <td>2.4078%</td>\n",
       "      <td>0.9815%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.6502%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.3024%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.5452%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.0225%</td>\n",
       "      <td>5.1519%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.6635%</td>\n",
       "      <td>1.4141%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8523%</td>\n",
       "      <td>8.2123%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.5285%</td>\n",
       "      <td>11.5853%</td>\n",
       "      <td>1.6263%</td>\n",
       "      <td>1.4953%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.6298%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6707%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.1893%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2024%</td>\n",
       "      <td>5.3155%</td>\n",
       "      <td>0.0771%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5638%</td>\n",
       "      <td>1.1082%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.3064%</td>\n",
       "      <td>8.9462%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0093%</td>\n",
       "      <td>11.9273%</td>\n",
       "      <td>0.8756%</td>\n",
       "      <td>1.9174%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8954%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9660%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.3812%</td>\n",
       "      <td>5.4381%</td>\n",
       "      <td>0.4351%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3775%</td>\n",
       "      <td>0.7796%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 1.9932% 4.4200% 3.5980%  8.4944% 5.0090% 0.0000% 0.0000%   \n",
       "1 0.0000% 1.6594% 6.2598% 1.2539% 3.4249% 10.4169% 3.1169% 0.3979% 0.0000%   \n",
       "2 0.0000% 2.3023% 7.3159% 0.0000% 3.0349% 11.1003% 2.4078% 0.9815% 0.0000%   \n",
       "3 0.0000% 2.8523% 8.2123% 0.0000% 2.5285% 11.5853% 1.6263% 1.4953% 0.0000%   \n",
       "4 0.0000% 3.3064% 8.9462% 0.0000% 2.0093% 11.9273% 0.8756% 1.9174% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 4.4334%  ... 12.0935% 0.0000% 13.3194% 1.0113% 8.3006% 4.0840% 0.0000%   \n",
       "1 2.5871%  ... 13.7064% 0.0000%  7.7371% 0.0000% 6.7064% 4.9334% 0.0000%   \n",
       "2 1.6502%  ... 14.3024% 0.0000%  5.5452% 0.0000% 6.0225% 5.1519% 0.0000%   \n",
       "3 0.6298%  ... 14.6707% 0.0000%  3.1893% 0.0000% 5.2024% 5.3155% 0.0771%   \n",
       "4 0.0000%  ... 14.8954% 0.0000%  0.9660% 0.0000% 4.3812% 5.4381% 0.4351%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 10.3126% 1.6683%  \n",
       "1 0.0000% 10.5790% 1.6514%  \n",
       "2 0.0000% 10.6635% 1.4141%  \n",
       "3 0.0000% 10.5638% 1.1082%  \n",
       "4 0.0000% 10.3775% 0.7796%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu_fm # Expected returns\n",
    "cov = port.cov_fm # Covariance matrix\n",
    "returns = port.returns_fm # Returns of the assets\n",
    "\n",
    "ax = rp.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                      rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                      marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Optimization with Constraints on Risk Factors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Statistics of Risk Factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "const    -0.0583%\n",
       "MTUM    -65.5123%\n",
       "QUAL    -59.9338%\n",
       "SIZE    -28.9787%\n",
       "USMV    -82.0339%\n",
       "VLUE    -49.1499%\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "const     0.0504%\n",
       "MTUM    103.0221%\n",
       "QUAL    117.4377%\n",
       "SIZE     94.0620%\n",
       "USMV    232.5673%\n",
       "VLUE    172.3679%\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MTUM</th>\n",
       "      <th>QUAL</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>USMV</th>\n",
       "      <th>VLUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MTUM</th>\n",
       "      <td>100.0000%</td>\n",
       "      <td>90.4264%</td>\n",
       "      <td>79.1171%</td>\n",
       "      <td>87.2321%</td>\n",
       "      <td>78.5394%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUAL</th>\n",
       "      <td>90.4264%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>89.8167%</td>\n",
       "      <td>89.9554%</td>\n",
       "      <td>91.6580%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SIZE</th>\n",
       "      <td>79.1171%</td>\n",
       "      <td>89.8167%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>82.5078%</td>\n",
       "      <td>87.9110%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USMV</th>\n",
       "      <td>87.2321%</td>\n",
       "      <td>89.9554%</td>\n",
       "      <td>82.5078%</td>\n",
       "      <td>100.0000%</td>\n",
       "      <td>76.9677%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VLUE</th>\n",
       "      <td>78.5394%</td>\n",
       "      <td>91.6580%</td>\n",
       "      <td>87.9110%</td>\n",
       "      <td>76.9677%</td>\n",
       "      <td>100.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          MTUM      QUAL      SIZE      USMV      VLUE\n",
       "MTUM 100.0000%  90.4264%  79.1171%  87.2321%  78.5394%\n",
       "QUAL  90.4264% 100.0000%  89.8167%  89.9554%  91.6580%\n",
       "SIZE  79.1171%  89.8167% 100.0000%  82.5078%  87.9110%\n",
       "USMV  87.2321%  89.9554%  82.5078% 100.0000%  76.9677%\n",
       "VLUE  78.5394%  91.6580%  87.9110%  76.9677% 100.0000%"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Displaying factors statistics\n",
    "\n",
    "display(loadings.min())\n",
    "display(loadings.max())\n",
    "display(X.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Creating Constraints on Risk Factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Disabled</th>\n",
       "      <th>Factor</th>\n",
       "      <th>Sign</th>\n",
       "      <th>Value</th>\n",
       "      <th>Relative Factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>MTUM</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>-30.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>QUAL</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>80.0000%</td>\n",
       "      <td>USMV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>SIZE</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>40.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>USMV</td>\n",
       "      <td>&gt;=</td>\n",
       "      <td>80.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>VLUE</td>\n",
       "      <td>&lt;=</td>\n",
       "      <td>90.0000%</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Disabled Factor Sign     Value Relative Factor\n",
       "0     False   MTUM   <= -30.0000%                \n",
       "1     False   QUAL   <=  80.0000%            USMV\n",
       "2     False   SIZE   <=  40.0000%                \n",
       "3     False   USMV   >=  80.0000%                \n",
       "4     False   VLUE   <=  90.0000%                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating risk factors constraints\n",
    "\n",
    "constraints = {'Disabled': [False, False, False, False, False],\n",
    "               'Factor': ['MTUM', 'QUAL', 'SIZE', 'USMV', 'VLUE'],\n",
    "               'Sign': ['<=', '<=', '<=', '>=', '<='],\n",
    "               'Value': [-0.3, 0.8, 0.4, 0.8 , 0.9],\n",
    "               'Relative Factor': ['', 'USMV', '', '', '']}\n",
    "\n",
    "constraints = pd.DataFrame(constraints)\n",
    "\n",
    "display(constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "C, D = rp.factors_constraints(constraints, loadings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.5845%</td>\n",
       "      <td>1.4885%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>17.4857%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.0878%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.9661%</td>\n",
       "      <td>1.3795%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.3011%</td>\n",
       "      <td>4.4149%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5793%</td>\n",
       "      <td>2.0949%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE  \\\n",
       "weights 0.0000% 6.5845% 1.4885% 0.0000% 0.0000% 17.4857% 0.0000% 4.0878%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 13.9661% 1.3795% 0.0000% 0.0000% 0.3011% 4.4149%   \n",
       "\n",
       "            TMO     TXT       VZ    ZION  \n",
       "weights 0.0000% 0.0000% 10.5793% 2.0949%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "port.ainequality = C\n",
    "port.binequality = D\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check if the constraints are verified, I will make a regression among the portfolio returns and risk factors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "const     0.0229%\n",
      "MTUM    -30.0000%\n",
      "QUAL     15.3061%\n",
      "SIZE      1.7749%\n",
      "USMV     92.6876%\n",
      "VLUE     21.9819%\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "X1 = sm.add_constant(X)\n",
    "y = np.matrix(returns) * np.matrix(w)\n",
    "results = sm.OLS(y, X1).fit()\n",
    "coefs = results.params\n",
    "\n",
    "print(coefs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = rp.plot_pie(w=w, title='Sharpe FM Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                 height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9932%</td>\n",
       "      <td>4.4200%</td>\n",
       "      <td>3.5980%</td>\n",
       "      <td>8.4942%</td>\n",
       "      <td>5.0090%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.4333%</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0934%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>13.3194%</td>\n",
       "      <td>1.0120%</td>\n",
       "      <td>8.3004%</td>\n",
       "      <td>4.0840%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.3124%</td>\n",
       "      <td>1.6684%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.0521%</td>\n",
       "      <td>4.5022%</td>\n",
       "      <td>1.9689%</td>\n",
       "      <td>3.3299%</td>\n",
       "      <td>10.3897%</td>\n",
       "      <td>3.6705%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.9589%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.4549%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.1008%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.4168%</td>\n",
       "      <td>4.6592%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.8689%</td>\n",
       "      <td>1.9831%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.7532%</td>\n",
       "      <td>4.8591%</td>\n",
       "      <td>0.7460%</td>\n",
       "      <td>2.9453%</td>\n",
       "      <td>11.4509%</td>\n",
       "      <td>3.1270%</td>\n",
       "      <td>0.3809%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0693%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1330%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.2018%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1317%</td>\n",
       "      <td>4.7867%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.2908%</td>\n",
       "      <td>2.0814%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.2852%</td>\n",
       "      <td>5.0706%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.6020%</td>\n",
       "      <td>12.3061%</td>\n",
       "      <td>2.6913%</td>\n",
       "      <td>0.7940%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3261%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.6726%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.6659%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.8990%</td>\n",
       "      <td>4.8725%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.6312%</td>\n",
       "      <td>2.1415%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.7539%</td>\n",
       "      <td>5.1123%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.1857%</td>\n",
       "      <td>13.1595%</td>\n",
       "      <td>2.2589%</td>\n",
       "      <td>1.1578%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5348%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.1823%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.1060%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.6672%</td>\n",
       "      <td>4.9232%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>11.9726%</td>\n",
       "      <td>2.1893%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA     BAX     BMY   CMCSA      CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000% 1.9932% 4.4200% 3.5980%  8.4942% 5.0090% 0.0000% 0.0000%   \n",
       "1 0.0000% 1.0521% 4.5022% 1.9689% 3.3299% 10.3897% 3.6705% 0.0000% 0.0000%   \n",
       "2 0.0000% 1.7532% 4.8591% 0.7460% 2.9453% 11.4509% 3.1270% 0.3809% 0.0000%   \n",
       "3 0.0000% 2.2852% 5.0706% 0.0000% 2.6020% 12.3061% 2.6913% 0.7940% 0.0000%   \n",
       "4 0.0000% 2.7539% 5.1123% 0.0000% 2.1857% 13.1595% 2.2589% 1.1578% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 4.4333%  ... 12.0934% 0.0000% 13.3194% 1.0120% 8.3004% 4.0840% 0.0000%   \n",
       "1 2.9589%  ... 13.4549% 0.0000%  9.1008% 0.0000% 7.4168% 4.6592% 0.0000%   \n",
       "2 2.0693%  ... 14.1330% 0.0000%  7.2018% 0.0000% 7.1317% 4.7867% 0.0000%   \n",
       "3 1.3261%  ... 14.6726% 0.0000%  5.6659% 0.0000% 6.8990% 4.8725% 0.0000%   \n",
       "4 0.5348%  ... 15.1823% 0.0000%  4.1060% 0.0000% 6.6672% 4.9232% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000% 10.3124% 1.6684%  \n",
       "1 0.0000% 10.8689% 1.9831%  \n",
       "2 0.0000% 11.2908% 2.0814%  \n",
       "3 0.0000% 11.6312% 2.1415%  \n",
       "4 0.0000% 11.9726% 2.1893%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                      rf=rf, alpha=0.05, cmap='viridis', w=w, label=label,\n",
    "                      marker='*', s=16, c='r', height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "ax = rp.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>-0.6213%</td>\n",
       "      <td>0.0684%</td>\n",
       "      <td>0.7015%</td>\n",
       "      <td>0.1909%</td>\n",
       "      <td>0.4772%</td>\n",
       "      <td>0.9282%</td>\n",
       "      <td>0.9911%</td>\n",
       "      <td>0.1761%</td>\n",
       "      <td>0.2252%</td>\n",
       "      <td>0.1002%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.1711%</td>\n",
       "      <td>-0.1121%</td>\n",
       "      <td>0.8782%</td>\n",
       "      <td>0.3501%</td>\n",
       "      <td>0.6946%</td>\n",
       "      <td>0.1709%</td>\n",
       "      <td>0.5663%</td>\n",
       "      <td>-0.2138%</td>\n",
       "      <td>0.9752%</td>\n",
       "      <td>-0.3551%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-2.8767%</td>\n",
       "      <td>-1.2757%</td>\n",
       "      <td>-0.6189%</td>\n",
       "      <td>-0.9939%</td>\n",
       "      <td>-0.8928%</td>\n",
       "      <td>-0.5879%</td>\n",
       "      <td>-0.3664%</td>\n",
       "      <td>-1.6300%</td>\n",
       "      <td>-2.2664%</td>\n",
       "      <td>-1.2376%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0190%</td>\n",
       "      <td>-2.1654%</td>\n",
       "      <td>-0.0372%</td>\n",
       "      <td>-1.3275%</td>\n",
       "      <td>-1.3600%</td>\n",
       "      <td>-1.3348%</td>\n",
       "      <td>-1.0117%</td>\n",
       "      <td>-1.8914%</td>\n",
       "      <td>-0.9196%</td>\n",
       "      <td>-2.5117%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-2.6604%</td>\n",
       "      <td>-2.6675%</td>\n",
       "      <td>-1.9233%</td>\n",
       "      <td>-1.9592%</td>\n",
       "      <td>-1.9763%</td>\n",
       "      <td>-1.2059%</td>\n",
       "      <td>-0.9113%</td>\n",
       "      <td>-2.3281%</td>\n",
       "      <td>-2.6834%</td>\n",
       "      <td>-1.8334%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.8785%</td>\n",
       "      <td>-2.6707%</td>\n",
       "      <td>-1.0104%</td>\n",
       "      <td>-1.9321%</td>\n",
       "      <td>-1.3673%</td>\n",
       "      <td>-1.5868%</td>\n",
       "      <td>-2.5264%</td>\n",
       "      <td>-2.5834%</td>\n",
       "      <td>-1.1151%</td>\n",
       "      <td>-2.2577%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>-1.6387%</td>\n",
       "      <td>-1.2856%</td>\n",
       "      <td>-1.0493%</td>\n",
       "      <td>-0.9502%</td>\n",
       "      <td>-1.0563%</td>\n",
       "      <td>-1.0628%</td>\n",
       "      <td>-0.9908%</td>\n",
       "      <td>-1.2707%</td>\n",
       "      <td>-1.3400%</td>\n",
       "      <td>-1.0335%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.9976%</td>\n",
       "      <td>-1.3240%</td>\n",
       "      <td>-0.9136%</td>\n",
       "      <td>-1.2707%</td>\n",
       "      <td>-0.9352%</td>\n",
       "      <td>-0.7749%</td>\n",
       "      <td>-1.2534%</td>\n",
       "      <td>-1.3154%</td>\n",
       "      <td>-0.9451%</td>\n",
       "      <td>-1.1138%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>-2.1924%</td>\n",
       "      <td>-0.0562%</td>\n",
       "      <td>0.3345%</td>\n",
       "      <td>0.0940%</td>\n",
       "      <td>0.1556%</td>\n",
       "      <td>-0.0892%</td>\n",
       "      <td>-0.0997%</td>\n",
       "      <td>-0.6705%</td>\n",
       "      <td>-0.7531%</td>\n",
       "      <td>-0.5542%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2115%</td>\n",
       "      <td>-0.7574%</td>\n",
       "      <td>0.3162%</td>\n",
       "      <td>-0.5898%</td>\n",
       "      <td>-0.4232%</td>\n",
       "      <td>-0.4203%</td>\n",
       "      <td>0.3350%</td>\n",
       "      <td>-0.8258%</td>\n",
       "      <td>-0.1979%</td>\n",
       "      <td>-1.4464%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-20</th>\n",
       "      <td>0.9709%</td>\n",
       "      <td>0.6528%</td>\n",
       "      <td>0.7567%</td>\n",
       "      <td>0.4352%</td>\n",
       "      <td>0.6099%</td>\n",
       "      <td>0.6594%</td>\n",
       "      <td>0.6196%</td>\n",
       "      <td>0.9430%</td>\n",
       "      <td>1.0746%</td>\n",
       "      <td>0.6983%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5968%</td>\n",
       "      <td>0.7454%</td>\n",
       "      <td>0.4033%</td>\n",
       "      <td>0.7249%</td>\n",
       "      <td>0.7672%</td>\n",
       "      <td>0.6842%</td>\n",
       "      <td>0.7894%</td>\n",
       "      <td>0.7581%</td>\n",
       "      <td>0.7437%</td>\n",
       "      <td>0.9396%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>0.6972%</td>\n",
       "      <td>0.2477%</td>\n",
       "      <td>-0.4230%</td>\n",
       "      <td>-0.0181%</td>\n",
       "      <td>-0.1988%</td>\n",
       "      <td>-0.5600%</td>\n",
       "      <td>-0.7398%</td>\n",
       "      <td>0.1197%</td>\n",
       "      <td>0.1322%</td>\n",
       "      <td>0.0606%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.8528%</td>\n",
       "      <td>0.4842%</td>\n",
       "      <td>-0.6863%</td>\n",
       "      <td>-0.1715%</td>\n",
       "      <td>-0.3171%</td>\n",
       "      <td>0.1147%</td>\n",
       "      <td>-0.2473%</td>\n",
       "      <td>0.3183%</td>\n",
       "      <td>-0.5772%</td>\n",
       "      <td>0.6377%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>-0.1966%</td>\n",
       "      <td>0.0027%</td>\n",
       "      <td>0.1506%</td>\n",
       "      <td>-0.0503%</td>\n",
       "      <td>0.0391%</td>\n",
       "      <td>0.0930%</td>\n",
       "      <td>0.1006%</td>\n",
       "      <td>0.0558%</td>\n",
       "      <td>-0.0071%</td>\n",
       "      <td>0.0206%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1566%</td>\n",
       "      <td>-0.1185%</td>\n",
       "      <td>0.0728%</td>\n",
       "      <td>-0.0239%</td>\n",
       "      <td>0.0209%</td>\n",
       "      <td>0.0305%</td>\n",
       "      <td>0.0896%</td>\n",
       "      <td>-0.0882%</td>\n",
       "      <td>0.0778%</td>\n",
       "      <td>-0.0759%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-26</th>\n",
       "      <td>0.0838%</td>\n",
       "      <td>0.3934%</td>\n",
       "      <td>0.3568%</td>\n",
       "      <td>0.2717%</td>\n",
       "      <td>0.3344%</td>\n",
       "      <td>0.2787%</td>\n",
       "      <td>0.1966%</td>\n",
       "      <td>0.3100%</td>\n",
       "      <td>0.3689%</td>\n",
       "      <td>0.2053%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2525%</td>\n",
       "      <td>0.3537%</td>\n",
       "      <td>0.2093%</td>\n",
       "      <td>0.2124%</td>\n",
       "      <td>0.2761%</td>\n",
       "      <td>0.2577%</td>\n",
       "      <td>0.4285%</td>\n",
       "      <td>0.2202%</td>\n",
       "      <td>0.2812%</td>\n",
       "      <td>0.2258%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-27</th>\n",
       "      <td>-0.7230%</td>\n",
       "      <td>-0.0384%</td>\n",
       "      <td>0.2654%</td>\n",
       "      <td>-0.0101%</td>\n",
       "      <td>0.1392%</td>\n",
       "      <td>0.3665%</td>\n",
       "      <td>0.3917%</td>\n",
       "      <td>-0.1304%</td>\n",
       "      <td>-0.2432%</td>\n",
       "      <td>-0.1203%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5586%</td>\n",
       "      <td>-0.2998%</td>\n",
       "      <td>0.4283%</td>\n",
       "      <td>-0.0294%</td>\n",
       "      <td>0.0874%</td>\n",
       "      <td>-0.1121%</td>\n",
       "      <td>0.1726%</td>\n",
       "      <td>-0.3568%</td>\n",
       "      <td>0.2897%</td>\n",
       "      <td>-0.5416%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1003 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                APA       BA      BAX      BMY    CMCSA      CNP      CPB  \\\n",
       "2016-01-05 -0.6213%  0.0684%  0.7015%  0.1909%  0.4772%  0.9282%  0.9911%   \n",
       "2016-01-06 -2.8767% -1.2757% -0.6189% -0.9939% -0.8928% -0.5879% -0.3664%   \n",
       "2016-01-07 -2.6604% -2.6675% -1.9233% -1.9592% -1.9763% -1.2059% -0.9113%   \n",
       "2016-01-08 -1.6387% -1.2856% -1.0493% -0.9502% -1.0563% -1.0628% -0.9908%   \n",
       "2016-01-11 -2.1924% -0.0562%  0.3345%  0.0940%  0.1556% -0.0892% -0.0997%   \n",
       "...             ...      ...      ...      ...      ...      ...      ...   \n",
       "2019-12-20  0.9709%  0.6528%  0.7567%  0.4352%  0.6099%  0.6594%  0.6196%   \n",
       "2019-12-23  0.6972%  0.2477% -0.4230% -0.0181% -0.1988% -0.5600% -0.7398%   \n",
       "2019-12-24 -0.1966%  0.0027%  0.1506% -0.0503%  0.0391%  0.0930%  0.1006%   \n",
       "2019-12-26  0.0838%  0.3934%  0.3568%  0.2717%  0.3344%  0.2787%  0.1966%   \n",
       "2019-12-27 -0.7230% -0.0384%  0.2654% -0.0101%  0.1392%  0.3665%  0.3917%   \n",
       "\n",
       "                 DE      HPQ      JCI  ...       NI     PCAR      PSA  \\\n",
       "2016-01-05  0.1761%  0.2252%  0.1002%  ...  1.1711% -0.1121%  0.8782%   \n",
       "2016-01-06 -1.6300% -2.2664% -1.2376%  ... -0.0190% -2.1654% -0.0372%   \n",
       "2016-01-07 -2.3281% -2.6834% -1.8334%  ... -0.8785% -2.6707% -1.0104%   \n",
       "2016-01-08 -1.2707% -1.3400% -1.0335%  ... -0.9976% -1.3240% -0.9136%   \n",
       "2016-01-11 -0.6705% -0.7531% -0.5542%  ...  0.2115% -0.7574%  0.3162%   \n",
       "...             ...      ...      ...  ...      ...      ...      ...   \n",
       "2019-12-20  0.9430%  1.0746%  0.6983%  ...  0.5968%  0.7454%  0.4033%   \n",
       "2019-12-23  0.1197%  0.1322%  0.0606%  ... -0.8528%  0.4842% -0.6863%   \n",
       "2019-12-24  0.0558% -0.0071%  0.0206%  ...  0.1566% -0.1185%  0.0728%   \n",
       "2019-12-26  0.3100%  0.3689%  0.2053%  ...  0.2525%  0.3537%  0.2093%   \n",
       "2019-12-27 -0.1304% -0.2432% -0.1203%  ...  0.5586% -0.2998%  0.4283%   \n",
       "\n",
       "                SEE        T      TGT      TMO      TXT       VZ     ZION  \n",
       "2016-01-05  0.3501%  0.6946%  0.1709%  0.5663% -0.2138%  0.9752% -0.3551%  \n",
       "2016-01-06 -1.3275% -1.3600% -1.3348% -1.0117% -1.8914% -0.9196% -2.5117%  \n",
       "2016-01-07 -1.9321% -1.3673% -1.5868% -2.5264% -2.5834% -1.1151% -2.2577%  \n",
       "2016-01-08 -1.2707% -0.9352% -0.7749% -1.2534% -1.3154% -0.9451% -1.1138%  \n",
       "2016-01-11 -0.5898% -0.4232% -0.4203%  0.3350% -0.8258% -0.1979% -1.4464%  \n",
       "...             ...      ...      ...      ...      ...      ...      ...  \n",
       "2019-12-20  0.7249%  0.7672%  0.6842%  0.7894%  0.7581%  0.7437%  0.9396%  \n",
       "2019-12-23 -0.1715% -0.3171%  0.1147% -0.2473%  0.3183% -0.5772%  0.6377%  \n",
       "2019-12-24 -0.0239%  0.0209%  0.0305%  0.0896% -0.0882%  0.0778% -0.0759%  \n",
       "2019-12-26  0.2124%  0.2761%  0.2577%  0.4285%  0.2202%  0.2812%  0.2258%  \n",
       "2019-12-27 -0.0294%  0.0874% -0.1121%  0.1726% -0.3568%  0.2897% -0.5416%  \n",
       "\n",
       "[1003 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(returns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Estimating Portfolios Using Risk Factors with Other Risk Measures\n",
    "\n",
    "In this part I will calculate optimal portfolios for several risk measures. I will find the portfolios that maximize the risk adjusted return for all available risk measures.\n",
    "\n",
    "### 4.1 Calculate Optimal Portfolios for Several Risk Measures.\n",
    "\n",
    "I will mantain the constraints on risk factors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Risk Measures available:\n",
    "#\n",
    "# 'MV': Standard Deviation.\n",
    "# 'MAD': Mean Absolute Deviation.\n",
    "# 'MSV': Semi Standard Deviation.\n",
    "# 'FLPM': First Lower Partial Moment (Omega Ratio).\n",
    "# 'SLPM': Second Lower Partial Moment (Sortino Ratio).\n",
    "# 'CVaR': Conditional Value at Risk.\n",
    "# 'EVaR': Entropic Value at Risk.\n",
    "# 'WR': Worst Realization (Minimax)\n",
    "# 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).\n",
    "# 'ADD': Average Drawdown of uncompounded cumulative returns.\n",
    "# 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.\n",
    "# 'UCI': Ulcer Index of uncompounded cumulative returns.\n",
    "\n",
    "# port.reset_linear_constraints() # To reset linear constraints (factor constraints)\n",
    "\n",
    "rms = ['MV', 'MAD', 'MSV', 'FLPM', 'SLPM', 'CVaR',\n",
    "       'EVaR', 'WR', 'MDD', 'ADD', 'CDaR', 'UCI', 'EDaR']\n",
    "\n",
    "w_s = pd.DataFrame([])\n",
    "\n",
    "# When we use hist = True the risk measures all calculated\n",
    "# using historical returns, while when hist = False the\n",
    "# risk measures are calculated using the expected returns \n",
    "#  based on risk factor model: R = a + B * F\n",
    "\n",
    "hist = False\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "#T_442e5_row0_col0, #T_442e5_row0_col1, #T_442e5_row0_col2, #T_442e5_row0_col3, #T_442e5_row0_col4, #T_442e5_row0_col5, #T_442e5_row0_col6, #T_442e5_row0_col7, #T_442e5_row0_col8, #T_442e5_row0_col9, #T_442e5_row0_col10, #T_442e5_row0_col11, #T_442e5_row0_col12, #T_442e5_row1_col1, #T_442e5_row1_col2, #T_442e5_row1_col3, #T_442e5_row1_col4, #T_442e5_row1_col5, #T_442e5_row1_col6, #T_442e5_row1_col7, #T_442e5_row1_col8, #T_442e5_row1_col9, #T_442e5_row1_col10, #T_442e5_row1_col11, #T_442e5_row1_col12, #T_442e5_row2_col1, #T_442e5_row2_col2, #T_442e5_row2_col3, #T_442e5_row2_col4, #T_442e5_row2_col5, #T_442e5_row2_col6, #T_442e5_row2_col7, #T_442e5_row2_col8, #T_442e5_row2_col9, #T_442e5_row2_col10, #T_442e5_row2_col11, #T_442e5_row2_col12, #T_442e5_row3_col0, #T_442e5_row3_col1, #T_442e5_row3_col2, #T_442e5_row3_col3, #T_442e5_row3_col4, #T_442e5_row3_col5, #T_442e5_row3_col6, #T_442e5_row3_col7, #T_442e5_row3_col8, #T_442e5_row3_col9, #T_442e5_row3_col10, #T_442e5_row3_col11, 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#T_442e5_row8_col9, #T_442e5_row8_col10, #T_442e5_row8_col11, #T_442e5_row8_col12, #T_442e5_row9_col0, #T_442e5_row9_col1, #T_442e5_row9_col2, #T_442e5_row9_col3, #T_442e5_row9_col4, #T_442e5_row9_col5, #T_442e5_row9_col6, #T_442e5_row9_col7, #T_442e5_row9_col8, #T_442e5_row9_col9, #T_442e5_row9_col10, #T_442e5_row9_col11, #T_442e5_row9_col12, #T_442e5_row10_col1, #T_442e5_row10_col2, #T_442e5_row10_col3, #T_442e5_row10_col4, #T_442e5_row10_col5, #T_442e5_row10_col6, #T_442e5_row10_col7, #T_442e5_row10_col8, #T_442e5_row10_col9, #T_442e5_row10_col10, #T_442e5_row10_col11, #T_442e5_row10_col12, #T_442e5_row11_col0, #T_442e5_row11_col1, #T_442e5_row11_col2, #T_442e5_row11_col3, #T_442e5_row11_col4, #T_442e5_row11_col5, #T_442e5_row11_col6, #T_442e5_row11_col7, #T_442e5_row11_col8, #T_442e5_row11_col9, #T_442e5_row11_col10, #T_442e5_row11_col11, #T_442e5_row11_col12, #T_442e5_row12_col2, #T_442e5_row12_col4, #T_442e5_row12_col5, #T_442e5_row12_col6, #T_442e5_row12_col7, #T_442e5_row12_col8, #T_442e5_row12_col12, #T_442e5_row13_col0, #T_442e5_row13_col1, #T_442e5_row13_col2, #T_442e5_row13_col3, #T_442e5_row13_col4, #T_442e5_row13_col5, #T_442e5_row13_col6, #T_442e5_row13_col7, #T_442e5_row13_col8, #T_442e5_row13_col9, #T_442e5_row13_col10, #T_442e5_row13_col11, #T_442e5_row13_col12, #T_442e5_row14_col0, #T_442e5_row14_col1, #T_442e5_row14_col2, #T_442e5_row14_col3, #T_442e5_row14_col4, #T_442e5_row14_col5, #T_442e5_row14_col6, #T_442e5_row14_col7, #T_442e5_row14_col8, #T_442e5_row14_col9, #T_442e5_row14_col10, #T_442e5_row14_col11, #T_442e5_row14_col12, #T_442e5_row15_col1, #T_442e5_row15_col2, #T_442e5_row15_col3, #T_442e5_row15_col4, #T_442e5_row15_col6, #T_442e5_row15_col7, #T_442e5_row15_col9, #T_442e5_row15_col10, #T_442e5_row15_col11, #T_442e5_row16_col1, #T_442e5_row16_col2, #T_442e5_row16_col3, #T_442e5_row16_col4, #T_442e5_row16_col5, #T_442e5_row16_col6, #T_442e5_row16_col7, #T_442e5_row16_col8, #T_442e5_row16_col9, #T_442e5_row16_col10, #T_442e5_row16_col11, #T_442e5_row16_col12, #T_442e5_row17_col0, #T_442e5_row17_col1, #T_442e5_row17_col2, #T_442e5_row17_col3, #T_442e5_row17_col4, #T_442e5_row17_col5, #T_442e5_row17_col6, #T_442e5_row17_col7, #T_442e5_row17_col8, #T_442e5_row17_col9, #T_442e5_row17_col10, #T_442e5_row17_col11, #T_442e5_row17_col12, #T_442e5_row18_col0, #T_442e5_row18_col1, #T_442e5_row18_col2, #T_442e5_row18_col3, #T_442e5_row18_col4, #T_442e5_row18_col5, #T_442e5_row18_col6, #T_442e5_row18_col7, #T_442e5_row18_col8, #T_442e5_row18_col9, #T_442e5_row18_col10, #T_442e5_row18_col11, #T_442e5_row18_col12, #T_442e5_row19_col1, #T_442e5_row19_col2, #T_442e5_row19_col3, #T_442e5_row19_col4, #T_442e5_row19_col5, #T_442e5_row19_col6, #T_442e5_row19_col7, #T_442e5_row19_col8, #T_442e5_row19_col9, #T_442e5_row19_col10, #T_442e5_row19_col11, #T_442e5_row19_col12, #T_442e5_row21_col0, #T_442e5_row21_col1, #T_442e5_row21_col2, #T_442e5_row21_col3, #T_442e5_row21_col4, #T_442e5_row21_col5, #T_442e5_row21_col6, #T_442e5_row21_col7, #T_442e5_row21_col8, #T_442e5_row21_col9, #T_442e5_row21_col10, #T_442e5_row21_col11, #T_442e5_row21_col12, #T_442e5_row22_col0, #T_442e5_row22_col1, #T_442e5_row22_col2, #T_442e5_row22_col3, #T_442e5_row22_col4, #T_442e5_row22_col5, #T_442e5_row22_col6, #T_442e5_row22_col7, #T_442e5_row22_col8, #T_442e5_row22_col9, #T_442e5_row22_col10, #T_442e5_row22_col11, #T_442e5_row22_col12, #T_442e5_row23_col1, #T_442e5_row23_col2, #T_442e5_row23_col3, #T_442e5_row23_col4, #T_442e5_row23_col5, #T_442e5_row23_col6, #T_442e5_row23_col7, #T_442e5_row23_col8, #T_442e5_row23_col9, #T_442e5_row23_col10, #T_442e5_row23_col11, #T_442e5_row23_col12, #T_442e5_row24_col1, #T_442e5_row24_col2, #T_442e5_row24_col3, #T_442e5_row24_col4, #T_442e5_row24_col5, #T_442e5_row24_col6, #T_442e5_row24_col8, #T_442e5_row24_col9, #T_442e5_row24_col10, #T_442e5_row24_col11, #T_442e5_row24_col12 {\n",
       "  background-color: #ffffe5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row1_col0, #T_442e5_row24_col7 {\n",
       "  background-color: #ddf1a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row2_col0 {\n",
       "  background-color: #fcfed3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row5_col0 {\n",
       "  background-color: #42ab5d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row5_col1, #T_442e5_row5_col2, #T_442e5_row5_col3, #T_442e5_row5_col4, #T_442e5_row5_col6, #T_442e5_row5_col7, #T_442e5_row5_col9, #T_442e5_row5_col11, #T_442e5_row5_col12, #T_442e5_row12_col0, #T_442e5_row12_col10, #T_442e5_row15_col8, #T_442e5_row20_col5 {\n",
       "  background-color: #004529;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row5_col5 {\n",
       "  background-color: #00542f;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row5_col10 {\n",
       "  background-color: #a7db8c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row7_col0 {\n",
       "  background-color: #f2fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row10_col0 {\n",
       "  background-color: #b9e294;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row12_col1 {\n",
       "  background-color: #61bb6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row12_col3 {\n",
       "  background-color: #56b568;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row12_col9 {\n",
       "  background-color: #c9e99c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row12_col11 {\n",
       "  background-color: #c0e597;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row15_col0 {\n",
       "  background-color: #79c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row15_col5 {\n",
       "  background-color: #bae394;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row15_col12 {\n",
       "  background-color: #f7fcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row16_col0 {\n",
       "  background-color: #fcfed4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row19_col0 {\n",
       "  background-color: #feffe2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row20_col0 {\n",
       "  background-color: #eff9b3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row20_col1, #T_442e5_row20_col3 {\n",
       "  background-color: #13773d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row20_col2, #T_442e5_row20_col4, #T_442e5_row20_col6 {\n",
       "  background-color: #026a38;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row20_col7 {\n",
       "  background-color: #11753d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row20_col8 {\n",
       "  background-color: #62bb6e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row20_col9, #T_442e5_row20_col11 {\n",
       "  background-color: #0b713b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row20_col10 {\n",
       "  background-color: #ddf2a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row20_col12 {\n",
       "  background-color: #005830;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_442e5_row23_col0 {\n",
       "  background-color: #acdd8e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_442e5_row24_col0 {\n",
       "  background-color: #fafdcb;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_442e5\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_442e5_level0_col0\" class=\"col_heading level0 col0\" >MV</th>\n",
       "      <th id=\"T_442e5_level0_col1\" class=\"col_heading level0 col1\" >MAD</th>\n",
       "      <th id=\"T_442e5_level0_col2\" class=\"col_heading level0 col2\" >MSV</th>\n",
       "      <th id=\"T_442e5_level0_col3\" class=\"col_heading level0 col3\" >FLPM</th>\n",
       "      <th id=\"T_442e5_level0_col4\" class=\"col_heading level0 col4\" >SLPM</th>\n",
       "      <th id=\"T_442e5_level0_col5\" class=\"col_heading level0 col5\" >CVaR</th>\n",
       "      <th id=\"T_442e5_level0_col6\" class=\"col_heading level0 col6\" >EVaR</th>\n",
       "      <th id=\"T_442e5_level0_col7\" class=\"col_heading level0 col7\" >WR</th>\n",
       "      <th id=\"T_442e5_level0_col8\" class=\"col_heading level0 col8\" >MDD</th>\n",
       "      <th id=\"T_442e5_level0_col9\" class=\"col_heading level0 col9\" >ADD</th>\n",
       "      <th id=\"T_442e5_level0_col10\" class=\"col_heading level0 col10\" >CDaR</th>\n",
       "      <th id=\"T_442e5_level0_col11\" class=\"col_heading level0 col11\" >UCI</th>\n",
       "      <th id=\"T_442e5_level0_col12\" class=\"col_heading level0 col12\" >EDaR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_442e5_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_442e5_row1_col0\" class=\"data row1 col0\" >6.58%</td>\n",
       "      <td id=\"T_442e5_row1_col1\" class=\"data row1 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col2\" class=\"data row1 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col3\" class=\"data row1 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col4\" class=\"data row1 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col5\" class=\"data row1 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col6\" class=\"data row1 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col8\" class=\"data row1 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col9\" class=\"data row1 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col10\" class=\"data row1 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col11\" class=\"data row1 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row1_col12\" class=\"data row1 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_442e5_row2_col0\" class=\"data row2 col0\" >1.49%</td>\n",
       "      <td id=\"T_442e5_row2_col1\" class=\"data row2 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col2\" class=\"data row2 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col3\" class=\"data row2 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col4\" class=\"data row2 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col5\" class=\"data row2 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col6\" class=\"data row2 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col9\" class=\"data row2 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col11\" class=\"data row2 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row2_col12\" class=\"data row2 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_442e5_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col6\" class=\"data row3 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_442e5_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col6\" class=\"data row4 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_442e5_row5_col0\" class=\"data row5 col0\" >17.49%</td>\n",
       "      <td id=\"T_442e5_row5_col1\" class=\"data row5 col1\" >42.33%</td>\n",
       "      <td id=\"T_442e5_row5_col2\" class=\"data row5 col2\" >53.62%</td>\n",
       "      <td id=\"T_442e5_row5_col3\" class=\"data row5 col3\" >41.97%</td>\n",
       "      <td id=\"T_442e5_row5_col4\" class=\"data row5 col4\" >53.62%</td>\n",
       "      <td id=\"T_442e5_row5_col5\" class=\"data row5 col5\" >41.32%</td>\n",
       "      <td id=\"T_442e5_row5_col6\" class=\"data row5 col6\" >53.62%</td>\n",
       "      <td id=\"T_442e5_row5_col7\" class=\"data row5 col7\" >48.75%</td>\n",
       "      <td id=\"T_442e5_row5_col8\" class=\"data row5 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row5_col9\" class=\"data row5 col9\" >46.94%</td>\n",
       "      <td id=\"T_442e5_row5_col10\" class=\"data row5 col10\" >23.94%</td>\n",
       "      <td id=\"T_442e5_row5_col11\" class=\"data row5 col11\" >46.45%</td>\n",
       "      <td id=\"T_442e5_row5_col12\" class=\"data row5 col12\" >48.69%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_442e5_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col6\" class=\"data row6 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col7\" class=\"data row6 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_442e5_row7_col0\" class=\"data row7 col0\" >4.09%</td>\n",
       "      <td id=\"T_442e5_row7_col1\" class=\"data row7 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col2\" class=\"data row7 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col3\" class=\"data row7 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col4\" class=\"data row7 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col5\" class=\"data row7 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col6\" class=\"data row7 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col8\" class=\"data row7 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col9\" class=\"data row7 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col10\" class=\"data row7 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col11\" class=\"data row7 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row7_col12\" class=\"data row7 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_442e5_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_442e5_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_442e5_row10_col0\" class=\"data row10 col0\" >9.55%</td>\n",
       "      <td id=\"T_442e5_row10_col1\" class=\"data row10 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col2\" class=\"data row10 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col3\" class=\"data row10 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col4\" class=\"data row10 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col7\" class=\"data row10 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col9\" class=\"data row10 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col11\" class=\"data row10 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row10_col12\" class=\"data row10 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_442e5_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_442e5_row12_col0\" class=\"data row12 col0\" >28.07%</td>\n",
       "      <td id=\"T_442e5_row12_col1\" class=\"data row12 col1\" >23.46%</td>\n",
       "      <td id=\"T_442e5_row12_col2\" class=\"data row12 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col3\" class=\"data row12 col3\" >24.19%</td>\n",
       "      <td id=\"T_442e5_row12_col4\" class=\"data row12 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col5\" class=\"data row12 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col6\" class=\"data row12 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col7\" class=\"data row12 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col8\" class=\"data row12 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row12_col9\" class=\"data row12 col9\" >13.88%</td>\n",
       "      <td id=\"T_442e5_row12_col10\" class=\"data row12 col10\" >61.67%</td>\n",
       "      <td id=\"T_442e5_row12_col11\" class=\"data row12 col11\" >14.89%</td>\n",
       "      <td id=\"T_442e5_row12_col12\" class=\"data row12 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_442e5_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_442e5_row14_col0\" class=\"data row14 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col1\" class=\"data row14 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col2\" class=\"data row14 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col3\" class=\"data row14 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col4\" class=\"data row14 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col5\" class=\"data row14 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col6\" class=\"data row14 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col7\" class=\"data row14 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col8\" class=\"data row14 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col9\" class=\"data row14 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col10\" class=\"data row14 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col11\" class=\"data row14 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row14_col12\" class=\"data row14 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_442e5_row15_col0\" class=\"data row15 col0\" >13.97%</td>\n",
       "      <td id=\"T_442e5_row15_col1\" class=\"data row15 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col2\" class=\"data row15 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col3\" class=\"data row15 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col4\" class=\"data row15 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col5\" class=\"data row15 col5\" >14.81%</td>\n",
       "      <td id=\"T_442e5_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col8\" class=\"data row15 col8\" >64.54%</td>\n",
       "      <td id=\"T_442e5_row15_col9\" class=\"data row15 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col10\" class=\"data row15 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col11\" class=\"data row15 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row15_col12\" class=\"data row15 col12\" >5.92%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_442e5_row16_col0\" class=\"data row16 col0\" >1.38%</td>\n",
       "      <td id=\"T_442e5_row16_col1\" class=\"data row16 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col2\" class=\"data row16 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col3\" class=\"data row16 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col4\" class=\"data row16 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col7\" class=\"data row16 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col8\" class=\"data row16 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col9\" class=\"data row16 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col10\" class=\"data row16 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row16_col12\" class=\"data row16 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_442e5_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_442e5_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_442e5_row19_col0\" class=\"data row19 col0\" >0.30%</td>\n",
       "      <td id=\"T_442e5_row19_col1\" class=\"data row19 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col3\" class=\"data row19 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col11\" class=\"data row19 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_442e5_row20_col0\" class=\"data row20 col0\" >4.41%</td>\n",
       "      <td id=\"T_442e5_row20_col1\" class=\"data row20 col1\" >34.21%</td>\n",
       "      <td id=\"T_442e5_row20_col2\" class=\"data row20 col2\" >46.38%</td>\n",
       "      <td id=\"T_442e5_row20_col3\" class=\"data row20 col3\" >33.83%</td>\n",
       "      <td id=\"T_442e5_row20_col4\" class=\"data row20 col4\" >46.38%</td>\n",
       "      <td id=\"T_442e5_row20_col5\" class=\"data row20 col5\" >43.88%</td>\n",
       "      <td id=\"T_442e5_row20_col6\" class=\"data row20 col6\" >46.38%</td>\n",
       "      <td id=\"T_442e5_row20_col7\" class=\"data row20 col7\" >39.77%</td>\n",
       "      <td id=\"T_442e5_row20_col8\" class=\"data row20 col8\" >35.46%</td>\n",
       "      <td id=\"T_442e5_row20_col9\" class=\"data row20 col9\" >39.18%</td>\n",
       "      <td id=\"T_442e5_row20_col10\" class=\"data row20 col10\" >14.39%</td>\n",
       "      <td id=\"T_442e5_row20_col11\" class=\"data row20 col11\" >38.66%</td>\n",
       "      <td id=\"T_442e5_row20_col12\" class=\"data row20 col12\" >45.38%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_442e5_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col6\" class=\"data row21 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col9\" class=\"data row21 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row21_col12\" class=\"data row21 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_442e5_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_442e5_row23_col0\" class=\"data row23 col0\" >10.58%</td>\n",
       "      <td id=\"T_442e5_row23_col1\" class=\"data row23 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col2\" class=\"data row23 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col3\" class=\"data row23 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col4\" class=\"data row23 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col5\" class=\"data row23 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col9\" class=\"data row23 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col10\" class=\"data row23 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col11\" class=\"data row23 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row23_col12\" class=\"data row23 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_442e5_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_442e5_row24_col0\" class=\"data row24 col0\" >2.09%</td>\n",
       "      <td id=\"T_442e5_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col7\" class=\"data row24 col7\" >11.48%</td>\n",
       "      <td id=\"T_442e5_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col9\" class=\"data row24 col9\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col11\" class=\"data row24 col11\" >0.00%</td>\n",
       "      <td id=\"T_442e5_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x17f872e10>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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9jx495OrqqhUrVpRwsuvuv/9+vfnmm/rb3/6W6/rVq1dr/PjxprmMuLu7u+69914NGjRIjz32WJ7l043zDTnSlStXtGrVKsXExGjLli2qUqWKBg0apIiICFWrVs3R8XI4ceKEGjZsKFdXVz377LMKCwuTxWJRYmKi5s+fr8zMTO3ZsyfXUS8lrWrVqoqPj9f//M//5Lo+ISFBvXv31m+//VbCyXLn6uqq1NRUpyhwcnPo0CFNnjxZn376qfr166dXXnlFgYGBjo4lFxcXvfrqq7Zif+LEiZowYUKOeW/MMLIpW/aHUrGxsbYPpRYsWKADBw6oVq1ajo5nk5ycXKDtzDjHn5klJycrMDDQ9nrm+++/t3ud5erqaqoPJv71r39p/Pjxunbtmm2eobNnz8rV1VVvvPGGbd5ER/vhhx9Uq1atfF8nvvfee+rfv38JpspbXpc9v3LliiIjI/XRRx/p2rVrpnkN/tc5BnP7GmcXuiWZ964pcJKTk7VhwwZdvXpVbdq0sU1kLEn79u1TTEyM3n77bQcmzNvhw4cVHR2td999VxcuXFDXrl3Vs2dPPfHEE46OJknq3bu3FixYkOsn6oZhaO7cuXrxxRdtQ08dqWzZsnr99dc1atQoR0cpsjNnzui9995TTEyMDhw4YJpfcM4kLi6uQNuZdXSW2f3www9q0qSJateurXHjxqlmzZq25W+99ZZ++OEH7dy502Ev1EaNGqXNmzdr165duY62aNy4scLDw03zNyG3Fw83/uku6RcPN1OuXDlduXJF3bp1U2RkpDp27Gi6iZZvlJycrBEjRuiLL76wfX0tFos6duyoBQsWKDg42LEB/7/IyEj9/PPP2rhxo90pqpKUnp6ujh076v7773fYKYo3yuvFutkdP35cL730kuLi4tSxY0fNmjXLVB+gFaTYt1gspimib8SHUnefhIQEjRs3Trt27ZIkeXt769KlS3a/b7/44gvbqYFm8Ouvv2rlypU6fPiwJKlGjRrq0aOHqT4ALl26tF555RU9//zzOX4nnDhxQk8//bS+/vpr04zWLleunJKTk/OcfPuf//ynFi5caJrfXVu2bCnQdq1bty7mJP91VxQ4W7duVZcuXXTp0iVJ14fHx8XFqU+fPg5OVjhZWVn67LPPtHTpUn3++edONUfH4cOHVb16dUfHME2O22XPnj2meLETHh5eoBeSX331VQkluvNkZWXJarVq9erVSkpKksViUbVq1dSjRw8NGDDAFMO5/2rnzp2KjIxUYmKiXelQs2ZNLV26VM2bN3dYNmcabSE556fBc+bM0cCBA015FZybOXPmjH7++WcZhqHq1aub7hTmX3/9VQ899JA8PDw0cuRIu4J0wYIFSk9P13fffWeaNxgvv/yyJkyYYDfPmJmdPXtWr732mv71r3+pfv36+sc//qGWLVs6OtYdy4wfSr3xxhsaNWqUSpcuLen6+4gmTZrYrpp3/vx5TZw4UQsWLHBkTKfTu3dvNW/e3DYqzNvbW+vWrVNQUJAMw9Dbb7+t5OTkPEfvInerVq3SiBEjFBYWJqvVqvvvv1/S9VE3Y8aMUZ06dRQTE2Nb7mguLi5q0KCBhg4dqr59+zrVVdTM4q4ocFq3bi0fHx8tXrxYpUuX1uTJk7Vu3TodO3bM0dHydfr0aVWsWFHS9WGn//73v3X58mU9+uijqlmzplN8mpX9hzk6Olr79u1zdBxt3bq1QNuZ5fLBN7py5Yri4+N18eJFdejQIc8JN0vac889l+e6c+fOafny5UpPTzfFC7NsK1eu1Jo1a3T16lW1a9dOzzzzjKMj5ckwDHXr1k2ff/65HnzwQdWsWdN22eCDBw/qscce05o1axwdM1f79u3TTz/9JEmqXr263eXmHSkpKUlRUVGmH20B5OaXX37RyJEjtWHDBrvv3/bt2+udd94xzd8GSQoMDNTevXttr2feeecdDRw4sETnCyioN954Q//4xz/k7++v1157zdRzud3M6dOn9e6775rmNI+CMMuHUjee9ufj46N9+/bZTv88ceKE7r33XlO9pnEGoaGheu+999S0aVNJ1wuc/fv3276ue/fuVdeuXXX8+HFHxpTkfO8XTp48qWHDhmnjxo2aPn26EhIS9OWXX+q1117T6NGjTfUh386dOxUdHa0VK1bo6tWreuKJJxQZGVnyl+IupN9++02rVq3STz/9JIvFoho1auiJJ55Q1apVSzzLXVHgVKhQQVu3brUNfb148aJ8fHx06tQp032yJkkHDx7Uo48+qmPHjql69er68MMP1alTJ128eFEuLi66ePGiPvroI3Xv3t3RUfP05ZdfKjo6WmvWrJGfn5+eeOIJzZs3z9Gx7K4wkde3vllORZgwYYIyMjJsX7eMjAw1adJE33//vcqUKaNr165p48aNatasmYOT5u7atWuaP3++Zs6cKV9fX73yyivq3bu3o2NJkpYsWaLhw4erevXq8vT01P/93//phRde0KxZsxwdLVexsbEaM2aMPv744xx/4DZt2qTu3bvb3hSZxfnz57Vz505dvXpVjRs3Nu1IDLOPtpCuX9FtwoQJdoXj22+/bdqvqZT31Xx8fHwUFhamF154wTSnAUvXLx5QEDExMcWcpHDOnDljG9ofGhrq0MnB83LjKVQ3vhk2k+yrErZr1y7fK4ysXr26BFMVnGEY2rBhg6Kjo/Xxxx/Lx8fHVBOy38isH0rd+D17Y9FAgVM0pUuX1qFDh2yjRVevXq1OnTrZRuclJyerRo0apjjDwJneL/xVv379tHz5cpUtW1Y7duxQ3bp1HR0pT9nzvcbGxiohIUHBwcGKiIjQoEGDdN999zk6np0FCxZo3LhxysjIkK+vr22uTHd3d82ZM0dRUVElmueuKHByO//a29tbBw4cUEhIiAOT5a5z585yc3PTxIkT9d5772nt2rXq0KGDli5dKun6/A27d+/Wzp07HZzUXkpKim1yugsXLujMmTNasWKFqa40UrFiRXl7e2vw4MEaMGBAnm+AzDCcr06dOnrttdf02GOPSbr+Jv7555/X3r17FRgYqIiICJ08eVLr1q1zcNKc3n//fU2bNk2XL1/W3//+dz3zzDN2lxh3tLp166p79+62y0NarVaNGjXKNOcH36hDhw565JFHNGnSpFzXv/baa9qyZYu++OKLEk6WuwMHDqhz585KTU2VdP0N20cffWSa89oLUhy4ubnJ399f7du3t5uc3REmTJigBQsWqF+/fvL09NTy5cvVpk0bU15uM9uaNWtyLXD+/PNPffvtt4qNjVVcXJyefPJJB6TLycXFRUFBQWrQoEG+V/Qww1VHnK1sutmbYTMZPHhwgT6pjo2NLYE0BZeUlKSYmBhZrVb99ttv6tevnwYOHKjw8HCHXur2r5zpQykKnOJRqVIlrVixQm3atMl1/ebNm/Xkk0+aonR0pvcL0vUyf+TIkfr44481ZswYxcfHy8PDQ3FxcXr44YcdHe+mjhw5otjYWC1btkypqalq3769PvvsM0fHkiStW7dOjz/+uMaOHavnn39eVapUkXT9ipD//Oc/9a9//Usff/yxunTpUnKhjLuAxWIxvv76a2P//v22W9myZY1169bZLTOLihUr2vKcP3/esFgsxq5du2zrExMTDV9fXwelyyk+Pt5o3769UaZMGaNnz57GmjVrjPT0dMPNzc34/vvvHR3PTnp6uvHhhx8aHTp0MEqXLm306NHD+Oyzz4ysrCxHR8vB29vbOHz4sO1+7969jaefftp2f+/evUaVKlUcES1Pn3/+ufHggw8aPj4+xowZM4wLFy44OlKuypQpYxw5csR2/9q1a0apUqWM1NRUB6bKW+XKlY29e/fmuX7Pnj1G5cqVSy7QTXTu3Nlo2rSpsX37dmP37t3GY489ZoSFhTk6ls3gwYNvehs4cKDRqVMno3Tp0saLL77o0LzVqlUzli9fbrv/zTffGG5ubsa1a9ccmOrWvPPOO0bjxo0dHcNmxIgRRvny5Y0HH3zQmDdvnnH69GlHR8qTxWIxgoODjb/97W9G9+7d87yZhcViMU6cOGG77+XlZff7F0Vz5coV44MPPjAeeeQRw9PT0/jb3/5mrFy50pSvvQzDMGrXrm18/PHHtvsxMTFG+fLljaSkJCMrK8sYPHiw0aVLFwcm/K+bfc+mpaUZLi4ujojm1Lp162YMGTIkz/WDBg0yunbtWoKJ8uZM7xc+/fRTw9/f32jcuLGRmJhoGIZhXLhwwRg+fLjh7u5uTJ061bh69aqDU97c+fPnjUWLFhkVKlQw1c9Xq1atjKlTp+a5furUqUarVq1KMJFh3DUFjouLi2GxWPK8mekbxdn+cLi6uhqTJ082zp07Z7fcrC8isqWkpBgvv/yyUa1aNaNq1arGlClTTPULztfX1/jpp59s94ODg43o6Gjb/aNHjxqenp6OiJbDN998Y7Rp08bw9PQ0xo4da/z++++OjpSvG3/GDMPcbypKlSplHD9+PM/1v/32m+Hu7l6CifJ3zz332JXOp06dMlxcXIzz5887MFXRrF271ggICHBohlKlShm//vqr3TJPT08jJSXFQYlu3U8//WSUK1fO0THsZL8hbteunVGmTBnjySefNNavX2+6F+zOVDYZxvXftzNnzjTmzZtnzJs3z/D09DRefPFF2/3sGwqnYsWKRsuWLY3Fixcbf/zxh225WV97OdOHUjf7nn311VdN9TrcWWzatMlwcXExxo8fb/ca7MSJE8a4ceMMV1dX46uvvnJgwtyZ/f2Ch4eHMXPmTCMzMzPHug0bNhiBgYHGgw8+WPLBCmjz5s3GwIEDjbJlyxo+Pj7G0KFDjf/85z+OjmXj7e1tHDp0KM/1hw4dMry8vEowkWHcFadQFeQKHmfOnFH9+vWLP0wBuLi46MSJE7rnnnsk5Tzdy2xDN5955hmtWLFCtWvX1oABA9SrVy+VL19epUqV0v79++0u2W5GR48eVWRkpLZs2aLff//dNHMING3aVE899ZTGjRun77//XvXq1dPPP/9s+z7YsmWLBg0apKSkJMcG1X/nDRg2bFi+k79mX3nA0VxcXPTqq6/Ky8vLtmzixImaMGGC3TBZs+R1dXVVWlqa7XfCjcz2O8HZTlvNz59//qmIiAiHznmR2/9/Z/16Zjtw4IA6duxoO83ObJKTk2W1WrVs2TJdvXpVP/zwg93vC0dLT0/X6tWrFRMTox07dqhr166KjIxUhw4dTDVZpeT8l7s2q/Lly6tevXrq37+/evXqZZsU2qyvvcqVK6ddu3bZrgQaEhKiF1980XZKYFJSkmrVqqXLly87Mqakgn3PStdfP6JwFixYoOeee07Xrl2Tj4+PLBaLzp49Kzc3N82ePVvPPvusoyPmyazvFw4cOKB69erluf7cuXN67rnnFB0dXYKp8nfs2DFZrVZZrVYdPXpUzZs3V2RkpJ566imVLVvW0fHseHl56cCBA3me9vvLL7+oXr16unDhQollMs+kFMUor0urnj17Vu+//77tCklmefMjXT8PO/tyhVeuXNHw4cNt39BmmNzrr5YsWaJ58+ZpxYoViomJ0dixY9WxY0cZhqGsrCxHx8tVenq6Vq1apZiYGP3nP/9R165dtW7dOtP8Mpauny/ep08frVu3Tt9//726dOli92bts88+U+PGjR2Y8L8CAwNlsVjynR/CYrGYphAJDAzUv//9b7tl/v7+evfdd233zZTXMAy73wk3MtvvBIvFovPnz8vT01PS9fzZy86dO2fbzoxXoblRuXLlHD5haW7//2/8uyCZd2LV3CxZssQ0H5rkxmKxyGKxmPbvmIeHh/r06aM+ffrYyqaoqChTlk1m+JDhTpSamqpVq1YpOjpaY8aMUefOndW/f3/TFXjZatasqU8//dT2oVRKSordpPzJycmqXLmyAxP+F9+zxScqKkqPPvqoPvroI9sE7NWrV1fPnj0VEBDg4HQ5OcP7hblz52revHny9vbOdb2Pj4+pypv27dvr66+/1j333KOBAwcqIiJCYWFhjo6Vp9q1a+vjjz/O84q7a9asUe3atUs0010xAudGmzZtUkxMjFavXq2goCD16NFDPXr0MM3lbYcMGVKg7cw2iV62w4cPKzo6Wu+++64uXLigrl27qmfPnqa44kj25JkffvihQkJCNHjwYPXv399Uv4j/6ssvv9S6devk7++vUaNG2Wbql6SXX35ZrVu3znMyONw5nO13Qm5XIMoucf76bzOV5mbmjBOrjhs3LtflZ8+e1XfffacjR44oISHBNH93JftRLdu2bVO3bt00ZMgQderUSS4uLo6Ol6eUlBTbJ5kZGRk6dOiQqQocFL/sCUDj4uL022+/qU+fPho8eLAeeeQR00xivGrVKvXp00ctW7bU//3f/+nhhx/W2rVrbesnTpyoo0ePasWKFQ5Med0333yjP/74Q507d7YtW7ZsmV566SVdvHhR3bt317/+9a88P1RB7iIiIvItGszEmd4v3HjZe7N77LHHFBkZqW7dupnm91N+4uLiNGLECL355pt2F2W5du2aFi9ebLvQxODBg0ss011T4Pz666+yWq2KiYnRxYsX9dRTT2nRokWmHGZ6p8jKytJnn32mpUuX6vPPPzfFKAEXFxcFBgZq0KBBatSoUZ7bZV/5CQWzadMmPfvss9q5c2eOURVnz55V8+bNtWjRIrVs2dJBCe05W15ns2XLlgJt17p162JOAke58XL32Xx8fFSzZk1169ZNsbGxprlSUlRUlD788EMFBgZqyJAh6t+/vypWrOjoWHlyprKJN8MlJysrS1988YWio6P16aefysvLS6dPn3Z0LJuvvvpKa9euVZUqVTRq1CiVLl3ats5MH0p16tRJ4eHhmjhxoiTp4MGDatiwoQYPHqxatWrpn//8p4YNG6bp06c7NqiTcaaiwZneL+R22jpur/Hjx2vOnDny9vbW/fffL+l6cX7hwgWNHj1ab731VonmuSsKnC5duthe4PTr10+dOnWSq6urac8TdlanT5+2veA9duyY/v3vf+vy5ct69NFHVbNmTVP8YinIC1uzjAw4fPiwpk2bpsWLF+daMowYMUKvvvqqKS7F+thjjyk8PDzP4YVvv/22vv76a1NcgldyvrzO5q+nSeXHGU6hMgNnu+x5Qezfv18NGzY0xe9a6b8v1hs0aJDvaCcznKbmbGVT586d1aZNG94Ml7BTp05p2bJleY6GK2mXL1/W+PHjtWbNGl29elXt2rXT22+/neflmR2pSpUq+vTTT/XQQw9JkqZOnaotW7Zo27ZtkqSVK1fqpZde0g8//ODImE7HmYoGZ3q/cOPcqSgeO3fu1PLly22n/tWoUUO9e/dW06ZNSzzLXVHguLm5afTo0RoxYoRt8jTJvBO9OZuDBw/q0Ucf1bFjx1S9enV9+OGH6tSpky5evCgXFxddvHhRH330kbp37+7oqE7lmWeeUbly5fTGG2/kun7ixIk6d+6cFi5cWMLJcgoKCtL69etVq1atXNcfOnRIHTp0UEpKSgkny52z5XU2uZ1ClRszvPBxBgU5hS4rK0snT57Uli1bNH78eM2YMaMEkhWd2QocZzpNzZnKJok3w8XlzJkzeu+99zRo0KBcP+RZtmxZruscJfs0g379+ql06dL64IMP1KZNG61cudLR0XLw9PTU4cOHbXOy/M///I86deqkv//975Kuz5FTt25dnT9/3pExnQ5FQ/FwcXGRr6/vTf+G/fHHHyWUCMXtrpjEOCEhQTExMXrooYdUs2ZN25WScHu88MILqlu3rt577z2999576tatm7p06aKlS5dKkkaNGqXXX3/dVAVObqOFrly5okcffdQ0p81s3brVblLdGz311FPq27dvCSbK24kTJ1SqVKk817u5uen3338vwUT5c7a8zubrr7+2/dswDNvvg6pVqzowlfMqTGmwbt06jRgxwvQFjtlYrVZHRyiwgQMHmnai2tycOXPGbnLaLVu2qFOnTrb7Dz/8sI4dO+aIaE7tnXfe0YEDBzRq1Kgc63x9fZWQkKDz589rypQpDkiX0+rVqxUdHa3evXtLkvr166cWLVooMzPTdPNgVK5cWUePHlVAQIAyMjK0Z88evfzyy7b158+fz/c1BPJWo0YNpyganGm+Hun6KYi+vr6OjnFHOnDgQIG2y+9KYLfbXVHgNGvWTM2aNdO8efP04YcfKiYmRuPGjVNWVpY2btyogIAAp/kBNaNdu3Zp06ZNqlevnurXr68lS5YoKirKNvxw1KhRDhlelpubjRaaM2eOaUYLJScn5zvM1M/PzzQveqtWraqDBw8qNDQ01/UHDhxQlSpVSjhV3pwtr7O5cW4bV1dXNW3a1BSn+93pWrRoYRvpgILLvpRxfiwWiymu5OFMZZPEm+HismrVKs2ePTvP9cOGDdP48eNNU+AcO3bM7gOyxo0by83NTcePHzfd1Yc6deqkSZMm6R//+IfWrFmjMmXK2GU/cOCAbR4MFI6zFA1xcXF6/fXXneb9Ye/evZ3i1DRnVL9+fdtVKfNS0qfT3RUFTrYyZcooIiJCERER+vHHHxUdHa3XX39dkyZNUvv27fXJJ584OqJT+uOPP+Tv7y9J8vLyUtmyZe1maS9fvrxphpk602ghX19fHTlyREFBQbmu//nnn00zNLpLly6aNm2aOnfubLt0dLbLly/rpZdeUrdu3RyULidnywsUlBkuey7dfN6eP//8s2SCFJDValVQUJAaNGiQ74s0FB5vhovHkSNH7KYFuFH16tV15MiREkyUv8zMTLm7u9stc3Nz07Vr1xyUKG+vvvqqnnjiCbVu3VpeXl6Ki4uzyx4TE6MOHTo4MKHzcpaiwZn+DjjTiExndPToUUdHyOGumAMnP5mZmfr0008VExNDgVNEN57T6u3trQMHDigkJETS9dNV7r33XlPMdeDn52cbLXThwgX5+Pjo22+/tX1ifejQITVt2tQUby6eeuopXb16Nc+JdB9//HG5u7ub4vzxEydOqGHDhnJ1ddWzzz6rsLAwWSwWJSYmav78+crMzNSePXvshtE7krPldXbe3t7av38/I3DuIgWZt0cyx5wykv3EwBEREaa9XKwz+v333/XEE09o+/bt8vLyktVqtSv42rZtq6ZNm2rmzJkOTOl8ypUrp/Xr1+c5wnnnzp3q1KmTKV7PSNdfK3bu3NnuamOffvqpHnnkEZUtW9a2zAwFdLazZ8/Ky8srxylef/zxh7y8vHIUUsifs12Fylnm63GmyaGdUdu2bTVy5Mg8P5g6deqUGjdurF9++aXEMt31BQ5u3Y1/lG/8g5yenq7169ebosC58ZfcjW8szVQ27d27V82aNVO3bt30wgsvKCwsTNL1kumNN97QunXrtGPHDjVs2NDBSa9LTk7WiBEj9MUXX9g+ubBYLOrYsaMWLFig4OBgxwa8gbPldWY3lrqAGf310tw7duxQ165dFRkZqQ4dOvAJ522Q35thb29vTqMqpPDwcDVp0kSvv/56rusnTpyob7/91m5OMkdytlIXt58zFQ1MDIxsLi4ucnFx0dSpU+1O/83miPeOFDi4Zc70R9mZRgtJ0tq1axUREaHTp0/bLa9YsaKWLl2qxx57zEHJ8nbmzBn9/PPPMgxD1atXV/ny5R0dKV/OltcZ3PgpRW6fskrm+qQV+Kvk5GRZrVYtW7ZMV69e1Q8//CAvLy9Hx3JKBZlfSLp+WgoKbtWqVerdu7feeustjRgxwlaMZWZmasGCBXr++ef1wQcfqGfPng5OCjgfFxcXzZ0796bz9QwaNKiEEsFRXFxctHjxYk2YMEHh4eF699137V4PUOAAxcyZRgtlu3z5stavX28rGWrUqKEOHTqoTJkyjo4G5MqZSl0gNykpKbJarbJarcrIyNChQ4cocIrIxcWlQPML5XW6MPI2depUzZo1S97e3qpWrZosFouOHDmiCxcuaMKECXmOzgGQP2caLYTilf29cPr0aXX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      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_s = pd.DataFrame([])\n",
    "\n",
    "# When we use hist = True the risk measures all calculated\n",
    "# using historical returns, while when hist = False the\n",
    "# risk measures are calculated using the expected returns \n",
    "#  based on risk factor model: R = a + B * F\n",
    "\n",
    "hist = True\n",
    "for i in rms:\n",
    "    w = port.optimization(model=model, rm=i, obj=obj, rf=rf, l=l, hist=hist)\n",
    "    w_s = pd.concat([w_s, w], axis=1)\n",
    "    \n",
    "w_s.columns = rms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col2, #T_6cdde_row1_col5 {\n",
       "  background-color: #ddf2a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col3, #T_6cdde_row20_col5 {\n",
       "  background-color: #e1f3a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col4, #T_6cdde_row23_col10 {\n",
       "  background-color: #ddf1a6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col6 {\n",
       "  background-color: #e8f6ae;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col8 {\n",
       "  background-color: #f6fcb8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col9 {\n",
       "  background-color: #abdc8d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col10 {\n",
       "  background-color: #81ca7d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col11, #T_6cdde_row23_col3 {\n",
       "  background-color: #9cd687;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row1_col12 {\n",
       "  background-color: #e6f5ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row2_col0, #T_6cdde_row2_col3 {\n",
       "  background-color: #fdfeda;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row2_col1 {\n",
       "  background-color: #fcfed7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row2_col2, #T_6cdde_row6_col6, #T_6cdde_row16_col4 {\n",
       "  background-color: #feffe2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row2_col4, #T_6cdde_row19_col3, #T_6cdde_row20_col10 {\n",
       "  background-color: #ffffe4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row2_col5, #T_6cdde_row7_col3 {\n",
       "  background-color: #f9fdc4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col0 {\n",
       "  background-color: #66bd70;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col1 {\n",
       "  background-color: #9ad587;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col2 {\n",
       "  background-color: #7cc87b;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col3 {\n",
       "  background-color: #97d385;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col4 {\n",
       "  background-color: #77c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col5 {\n",
       "  background-color: #56b568;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col6 {\n",
       "  background-color: #2d914b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col7 {\n",
       "  background-color: #006435;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col8, #T_6cdde_row5_col12, #T_6cdde_row12_col0, #T_6cdde_row12_col1, #T_6cdde_row12_col2, #T_6cdde_row12_col3, #T_6cdde_row12_col4, #T_6cdde_row12_col5, #T_6cdde_row12_col6, #T_6cdde_row12_col7, #T_6cdde_row12_col9, #T_6cdde_row12_col10, #T_6cdde_row12_col11 {\n",
       "  background-color: #004529;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col9, #T_6cdde_row10_col1 {\n",
       "  background-color: #c0e597;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row5_col10 {\n",
       "  background-color: #12763d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row5_col11, #T_6cdde_row15_col1 {\n",
       "  background-color: #8bce81;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row6_col7, #T_6cdde_row20_col4 {\n",
       "  background-color: #e2f4aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col0 {\n",
       "  background-color: #f8fcbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col1, #T_6cdde_row20_col12 {\n",
       "  background-color: #fbfdcf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col2 {\n",
       "  background-color: #fafdcb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col4 {\n",
       "  background-color: #fafdc9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col5, #T_6cdde_row24_col11 {\n",
       "  background-color: #fafdc8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col6, #T_6cdde_row16_col9 {\n",
       "  background-color: #fdfed9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col8, #T_6cdde_row14_col10, #T_6cdde_row20_col9, #T_6cdde_row23_col9 {\n",
       "  background-color: #f9fdc2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row7_col11, #T_6cdde_row14_col7 {\n",
       "  background-color: #fdfedb;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col0 {\n",
       "  background-color: #dff3a8;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col2, #T_6cdde_row15_col5 {\n",
       "  background-color: #edf8b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col3 {\n",
       "  background-color: #b6e192;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col4 {\n",
       "  background-color: #eff9b3;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col9, #T_6cdde_row19_col11 {\n",
       "  background-color: #fcfed6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row10_col11 {\n",
       "  background-color: #f8fdc1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row12_col8 {\n",
       "  background-color: #ceeb9e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row12_col12, #T_6cdde_row15_col9 {\n",
       "  background-color: #5fba6c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_6cdde_row14_col8, #T_6cdde_row16_col12 {\n",
       "  background-color: #f1fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row14_col12 {\n",
       "  background-color: #f0f9b4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col0, #T_6cdde_row23_col0 {\n",
       "  background-color: #b8e293;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col2 {\n",
       "  background-color: #c4e799;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col3 {\n",
       "  background-color: #6bc072;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col4, #T_6cdde_row20_col6, #T_6cdde_row23_col2 {\n",
       "  background-color: #c9e99c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col10 {\n",
       "  background-color: #cfec9e;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col11 {\n",
       "  background-color: #9fd788;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row15_col12, #T_6cdde_row16_col7 {\n",
       "  background-color: #f7fcba;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row16_col0, #T_6cdde_row16_col10 {\n",
       "  background-color: #fdfedd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row16_col1, #T_6cdde_row16_col3 {\n",
       "  background-color: #f9fdc5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row16_col2 {\n",
       "  background-color: #feffdf;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row16_col8 {\n",
       "  background-color: #f3fab6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row19_col1 {\n",
       "  background-color: #fcfed4;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col0 {\n",
       "  background-color: #eaf7af;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col1 {\n",
       "  background-color: #f2fab5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col2 {\n",
       "  background-color: #e3f4aa;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col3 {\n",
       "  background-color: #edf8b2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col7 {\n",
       "  background-color: #79c679;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row20_col11 {\n",
       "  background-color: #fafdcc;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row23_col1 {\n",
       "  background-color: #b1df90;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row23_col4 {\n",
       "  background-color: #ccea9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row23_col5 {\n",
       "  background-color: #bae394;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row23_col11 {\n",
       "  background-color: #f4fbb7;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_6cdde_row24_col9 {\n",
       "  background-color: #e9f6af;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_6cdde\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_6cdde_level0_col0\" class=\"col_heading level0 col0\" >MV</th>\n",
       "      <th id=\"T_6cdde_level0_col1\" class=\"col_heading level0 col1\" >MAD</th>\n",
       "      <th id=\"T_6cdde_level0_col2\" class=\"col_heading level0 col2\" >MSV</th>\n",
       "      <th id=\"T_6cdde_level0_col3\" class=\"col_heading level0 col3\" >FLPM</th>\n",
       "      <th id=\"T_6cdde_level0_col4\" class=\"col_heading level0 col4\" >SLPM</th>\n",
       "      <th id=\"T_6cdde_level0_col5\" class=\"col_heading level0 col5\" >CVaR</th>\n",
       "      <th id=\"T_6cdde_level0_col6\" class=\"col_heading level0 col6\" >EVaR</th>\n",
       "      <th id=\"T_6cdde_level0_col7\" class=\"col_heading level0 col7\" >WR</th>\n",
       "      <th id=\"T_6cdde_level0_col8\" class=\"col_heading level0 col8\" >MDD</th>\n",
       "      <th id=\"T_6cdde_level0_col9\" class=\"col_heading level0 col9\" >ADD</th>\n",
       "      <th id=\"T_6cdde_level0_col10\" class=\"col_heading level0 col10\" >CDaR</th>\n",
       "      <th id=\"T_6cdde_level0_col11\" class=\"col_heading level0 col11\" >UCI</th>\n",
       "      <th id=\"T_6cdde_level0_col12\" class=\"col_heading level0 col12\" >EDaR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row0\" class=\"row_heading level0 row0\" >APA</th>\n",
       "      <td id=\"T_6cdde_row0_col0\" class=\"data row0 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col1\" class=\"data row0 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col2\" class=\"data row0 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col3\" class=\"data row0 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col4\" class=\"data row0 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col5\" class=\"data row0 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col6\" class=\"data row0 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col7\" class=\"data row0 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col8\" class=\"data row0 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col9\" class=\"data row0 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col10\" class=\"data row0 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col11\" class=\"data row0 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row0_col12\" class=\"data row0 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row1\" class=\"row_heading level0 row1\" >BA</th>\n",
       "      <td id=\"T_6cdde_row1_col0\" class=\"data row1 col0\" >7.45%</td>\n",
       "      <td id=\"T_6cdde_row1_col1\" class=\"data row1 col1\" >7.00%</td>\n",
       "      <td id=\"T_6cdde_row1_col2\" class=\"data row1 col2\" >8.25%</td>\n",
       "      <td id=\"T_6cdde_row1_col3\" class=\"data row1 col3\" >6.48%</td>\n",
       "      <td id=\"T_6cdde_row1_col4\" class=\"data row1 col4\" >8.43%</td>\n",
       "      <td id=\"T_6cdde_row1_col5\" class=\"data row1 col5\" >8.52%</td>\n",
       "      <td id=\"T_6cdde_row1_col6\" class=\"data row1 col6\" >8.42%</td>\n",
       "      <td id=\"T_6cdde_row1_col7\" class=\"data row1 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row1_col8\" class=\"data row1 col8\" >7.16%</td>\n",
       "      <td id=\"T_6cdde_row1_col9\" class=\"data row1 col9\" >14.01%</td>\n",
       "      <td id=\"T_6cdde_row1_col10\" class=\"data row1 col10\" >16.29%</td>\n",
       "      <td id=\"T_6cdde_row1_col11\" class=\"data row1 col11\" >15.08%</td>\n",
       "      <td id=\"T_6cdde_row1_col12\" class=\"data row1 col12\" >8.71%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row2\" class=\"row_heading level0 row2\" >BAX</th>\n",
       "      <td id=\"T_6cdde_row2_col0\" class=\"data row2 col0\" >1.03%</td>\n",
       "      <td id=\"T_6cdde_row2_col1\" class=\"data row2 col1\" >1.30%</td>\n",
       "      <td id=\"T_6cdde_row2_col2\" class=\"data row2 col2\" >0.36%</td>\n",
       "      <td id=\"T_6cdde_row2_col3\" class=\"data row2 col3\" >0.95%</td>\n",
       "      <td id=\"T_6cdde_row2_col4\" class=\"data row2 col4\" >0.22%</td>\n",
       "      <td id=\"T_6cdde_row2_col5\" class=\"data row2 col5\" >3.48%</td>\n",
       "      <td id=\"T_6cdde_row2_col6\" class=\"data row2 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col7\" class=\"data row2 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col8\" class=\"data row2 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col9\" class=\"data row2 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col10\" class=\"data row2 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col11\" class=\"data row2 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row2_col12\" class=\"data row2 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row3\" class=\"row_heading level0 row3\" >BMY</th>\n",
       "      <td id=\"T_6cdde_row3_col0\" class=\"data row3 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col1\" class=\"data row3 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col2\" class=\"data row3 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col3\" class=\"data row3 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col4\" class=\"data row3 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col5\" class=\"data row3 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col6\" class=\"data row3 col6\" >0.01%</td>\n",
       "      <td id=\"T_6cdde_row3_col7\" class=\"data row3 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col8\" class=\"data row3 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col9\" class=\"data row3 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col10\" class=\"data row3 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col11\" class=\"data row3 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row3_col12\" class=\"data row3 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row4\" class=\"row_heading level0 row4\" >CMCSA</th>\n",
       "      <td id=\"T_6cdde_row4_col0\" class=\"data row4 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col1\" class=\"data row4 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col2\" class=\"data row4 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col3\" class=\"data row4 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col4\" class=\"data row4 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col5\" class=\"data row4 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col6\" class=\"data row4 col6\" >0.01%</td>\n",
       "      <td id=\"T_6cdde_row4_col7\" class=\"data row4 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col8\" class=\"data row4 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col9\" class=\"data row4 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col10\" class=\"data row4 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col11\" class=\"data row4 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row4_col12\" class=\"data row4 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row5\" class=\"row_heading level0 row5\" >CNP</th>\n",
       "      <td id=\"T_6cdde_row5_col0\" class=\"data row5 col0\" >17.82%</td>\n",
       "      <td id=\"T_6cdde_row5_col1\" class=\"data row5 col1\" >13.25%</td>\n",
       "      <td id=\"T_6cdde_row5_col2\" class=\"data row5 col2\" >17.50%</td>\n",
       "      <td id=\"T_6cdde_row5_col3\" class=\"data row5 col3\" >12.81%</td>\n",
       "      <td id=\"T_6cdde_row5_col4\" class=\"data row5 col4\" >17.98%</td>\n",
       "      <td id=\"T_6cdde_row5_col5\" class=\"data row5 col5\" >21.30%</td>\n",
       "      <td id=\"T_6cdde_row5_col6\" class=\"data row5 col6\" >31.62%</td>\n",
       "      <td id=\"T_6cdde_row5_col7\" class=\"data row5 col7\" >29.80%</td>\n",
       "      <td id=\"T_6cdde_row5_col8\" class=\"data row5 col8\" >55.32%</td>\n",
       "      <td id=\"T_6cdde_row5_col9\" class=\"data row5 col9\" >11.75%</td>\n",
       "      <td id=\"T_6cdde_row5_col10\" class=\"data row5 col10\" >27.54%</td>\n",
       "      <td id=\"T_6cdde_row5_col11\" class=\"data row5 col11\" >16.60%</td>\n",
       "      <td id=\"T_6cdde_row5_col12\" class=\"data row5 col12\" >44.55%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row6\" class=\"row_heading level0 row6\" >CPB</th>\n",
       "      <td id=\"T_6cdde_row6_col0\" class=\"data row6 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col1\" class=\"data row6 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col2\" class=\"data row6 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col3\" class=\"data row6 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col4\" class=\"data row6 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col5\" class=\"data row6 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col6\" class=\"data row6 col6\" >0.49%</td>\n",
       "      <td id=\"T_6cdde_row6_col7\" class=\"data row6 col7\" >7.20%</td>\n",
       "      <td id=\"T_6cdde_row6_col8\" class=\"data row6 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col9\" class=\"data row6 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col10\" class=\"data row6 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col11\" class=\"data row6 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row6_col12\" class=\"data row6 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row7\" class=\"row_heading level0 row7\" >DE</th>\n",
       "      <td id=\"T_6cdde_row7_col0\" class=\"data row7 col0\" >3.77%</td>\n",
       "      <td id=\"T_6cdde_row7_col1\" class=\"data row7 col1\" >1.98%</td>\n",
       "      <td id=\"T_6cdde_row7_col2\" class=\"data row7 col2\" >2.68%</td>\n",
       "      <td id=\"T_6cdde_row7_col3\" class=\"data row7 col3\" >2.93%</td>\n",
       "      <td id=\"T_6cdde_row7_col4\" class=\"data row7 col4\" >2.82%</td>\n",
       "      <td id=\"T_6cdde_row7_col5\" class=\"data row7 col5\" >3.09%</td>\n",
       "      <td id=\"T_6cdde_row7_col6\" class=\"data row7 col6\" >1.64%</td>\n",
       "      <td id=\"T_6cdde_row7_col7\" class=\"data row7 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row7_col8\" class=\"data row7 col8\" >5.45%</td>\n",
       "      <td id=\"T_6cdde_row7_col9\" class=\"data row7 col9\" >0.07%</td>\n",
       "      <td id=\"T_6cdde_row7_col10\" class=\"data row7 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row7_col11\" class=\"data row7 col11\" >1.08%</td>\n",
       "      <td id=\"T_6cdde_row7_col12\" class=\"data row7 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row8\" class=\"row_heading level0 row8\" >HPQ</th>\n",
       "      <td id=\"T_6cdde_row8_col0\" class=\"data row8 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col1\" class=\"data row8 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col2\" class=\"data row8 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col3\" class=\"data row8 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col4\" class=\"data row8 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col5\" class=\"data row8 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col6\" class=\"data row8 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col7\" class=\"data row8 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col8\" class=\"data row8 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col9\" class=\"data row8 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col10\" class=\"data row8 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col11\" class=\"data row8 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row8_col12\" class=\"data row8 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row9\" class=\"row_heading level0 row9\" >JCI</th>\n",
       "      <td id=\"T_6cdde_row9_col0\" class=\"data row9 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col1\" class=\"data row9 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col2\" class=\"data row9 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col3\" class=\"data row9 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col4\" class=\"data row9 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col5\" class=\"data row9 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col6\" class=\"data row9 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col7\" class=\"data row9 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col8\" class=\"data row9 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col9\" class=\"data row9 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col10\" class=\"data row9 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row10\" class=\"row_heading level0 row10\" >JPM</th>\n",
       "      <td id=\"T_6cdde_row10_col0\" class=\"data row10 col0\" >7.34%</td>\n",
       "      <td id=\"T_6cdde_row10_col1\" class=\"data row10 col1\" >10.09%</td>\n",
       "      <td id=\"T_6cdde_row10_col2\" class=\"data row10 col2\" >6.11%</td>\n",
       "      <td id=\"T_6cdde_row10_col3\" class=\"data row10 col3\" >10.54%</td>\n",
       "      <td id=\"T_6cdde_row10_col4\" class=\"data row10 col4\" >5.68%</td>\n",
       "      <td id=\"T_6cdde_row10_col5\" class=\"data row10 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row10_col6\" class=\"data row10 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row10_col7\" class=\"data row10 col7\" >7.70%</td>\n",
       "      <td id=\"T_6cdde_row10_col8\" class=\"data row10 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row10_col9\" class=\"data row10 col9\" >1.63%</td>\n",
       "      <td id=\"T_6cdde_row10_col10\" class=\"data row10 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row10_col11\" class=\"data row10 col11\" >3.72%</td>\n",
       "      <td id=\"T_6cdde_row10_col12\" class=\"data row10 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row11\" class=\"row_heading level0 row11\" >LUV</th>\n",
       "      <td id=\"T_6cdde_row11_col0\" class=\"data row11 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col1\" class=\"data row11 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col2\" class=\"data row11 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col3\" class=\"data row11 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col4\" class=\"data row11 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col5\" class=\"data row11 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col6\" class=\"data row11 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col7\" class=\"data row11 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col8\" class=\"data row11 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col9\" class=\"data row11 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col10\" class=\"data row11 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row11_col12\" class=\"data row11 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row12\" class=\"row_heading level0 row12\" >MMC</th>\n",
       "      <td id=\"T_6cdde_row12_col0\" class=\"data row12 col0\" >32.90%</td>\n",
       "      <td id=\"T_6cdde_row12_col1\" class=\"data row12 col1\" >31.48%</td>\n",
       "      <td id=\"T_6cdde_row12_col2\" class=\"data row12 col2\" >35.58%</td>\n",
       "      <td id=\"T_6cdde_row12_col3\" class=\"data row12 col3\" >30.04%</td>\n",
       "      <td id=\"T_6cdde_row12_col4\" class=\"data row12 col4\" >35.91%</td>\n",
       "      <td id=\"T_6cdde_row12_col5\" class=\"data row12 col5\" >36.88%</td>\n",
       "      <td id=\"T_6cdde_row12_col6\" class=\"data row12 col6\" >44.65%</td>\n",
       "      <td id=\"T_6cdde_row12_col7\" class=\"data row12 col7\" >33.51%</td>\n",
       "      <td id=\"T_6cdde_row12_col8\" class=\"data row12 col8\" >15.77%</td>\n",
       "      <td id=\"T_6cdde_row12_col9\" class=\"data row12 col9\" >36.62%</td>\n",
       "      <td id=\"T_6cdde_row12_col10\" class=\"data row12 col10\" >34.04%</td>\n",
       "      <td id=\"T_6cdde_row12_col11\" class=\"data row12 col11\" >36.34%</td>\n",
       "      <td id=\"T_6cdde_row12_col12\" class=\"data row12 col12\" >24.79%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row13\" class=\"row_heading level0 row13\" >MO</th>\n",
       "      <td id=\"T_6cdde_row13_col0\" class=\"data row13 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col1\" class=\"data row13 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col2\" class=\"data row13 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col3\" class=\"data row13 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col4\" class=\"data row13 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col5\" class=\"data row13 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col6\" class=\"data row13 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col7\" class=\"data row13 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col8\" class=\"data row13 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col9\" class=\"data row13 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col10\" class=\"data row13 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row13_col12\" class=\"data row13 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row14\" class=\"row_heading level0 row14\" >MSFT</th>\n",
       "      <td id=\"T_6cdde_row14_col0\" class=\"data row14 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col1\" class=\"data row14 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col2\" class=\"data row14 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col3\" class=\"data row14 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col4\" class=\"data row14 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col5\" class=\"data row14 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col6\" class=\"data row14 col6\" >0.01%</td>\n",
       "      <td id=\"T_6cdde_row14_col7\" class=\"data row14 col7\" >0.96%</td>\n",
       "      <td id=\"T_6cdde_row14_col8\" class=\"data row14 col8\" >8.42%</td>\n",
       "      <td id=\"T_6cdde_row14_col9\" class=\"data row14 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col10\" class=\"data row14 col10\" >3.41%</td>\n",
       "      <td id=\"T_6cdde_row14_col11\" class=\"data row14 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row14_col12\" class=\"data row14 col12\" >6.91%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row15\" class=\"row_heading level0 row15\" >NI</th>\n",
       "      <td id=\"T_6cdde_row15_col0\" class=\"data row15 col0\" >11.41%</td>\n",
       "      <td id=\"T_6cdde_row15_col1\" class=\"data row15 col1\" >14.36%</td>\n",
       "      <td id=\"T_6cdde_row15_col2\" class=\"data row15 col2\" >11.04%</td>\n",
       "      <td id=\"T_6cdde_row15_col3\" class=\"data row15 col3\" >15.88%</td>\n",
       "      <td id=\"T_6cdde_row15_col4\" class=\"data row15 col4\" >10.65%</td>\n",
       "      <td id=\"T_6cdde_row15_col5\" class=\"data row15 col5\" >6.20%</td>\n",
       "      <td id=\"T_6cdde_row15_col6\" class=\"data row15 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row15_col7\" class=\"data row15 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row15_col8\" class=\"data row15 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row15_col9\" class=\"data row15 col9\" >20.34%</td>\n",
       "      <td id=\"T_6cdde_row15_col10\" class=\"data row15 col10\" >9.55%</td>\n",
       "      <td id=\"T_6cdde_row15_col11\" class=\"data row15 col11\" >14.85%</td>\n",
       "      <td id=\"T_6cdde_row15_col12\" class=\"data row15 col12\" >5.47%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row16\" class=\"row_heading level0 row16\" >PCAR</th>\n",
       "      <td id=\"T_6cdde_row16_col0\" class=\"data row16 col0\" >0.89%</td>\n",
       "      <td id=\"T_6cdde_row16_col1\" class=\"data row16 col1\" >2.93%</td>\n",
       "      <td id=\"T_6cdde_row16_col2\" class=\"data row16 col2\" >0.60%</td>\n",
       "      <td id=\"T_6cdde_row16_col3\" class=\"data row16 col3\" >2.70%</td>\n",
       "      <td id=\"T_6cdde_row16_col4\" class=\"data row16 col4\" >0.34%</td>\n",
       "      <td id=\"T_6cdde_row16_col5\" class=\"data row16 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row16_col6\" class=\"data row16 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row16_col7\" class=\"data row16 col7\" >4.18%</td>\n",
       "      <td id=\"T_6cdde_row16_col8\" class=\"data row16 col8\" >7.87%</td>\n",
       "      <td id=\"T_6cdde_row16_col9\" class=\"data row16 col9\" >1.39%</td>\n",
       "      <td id=\"T_6cdde_row16_col10\" class=\"data row16 col10\" >0.90%</td>\n",
       "      <td id=\"T_6cdde_row16_col11\" class=\"data row16 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row16_col12\" class=\"data row16 col12\" >6.73%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row17\" class=\"row_heading level0 row17\" >PSA</th>\n",
       "      <td id=\"T_6cdde_row17_col0\" class=\"data row17 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col1\" class=\"data row17 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col2\" class=\"data row17 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col3\" class=\"data row17 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col4\" class=\"data row17 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col5\" class=\"data row17 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col6\" class=\"data row17 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col7\" class=\"data row17 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col8\" class=\"data row17 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col9\" class=\"data row17 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col10\" class=\"data row17 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col11\" class=\"data row17 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row17_col12\" class=\"data row17 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row18\" class=\"row_heading level0 row18\" >SEE</th>\n",
       "      <td id=\"T_6cdde_row18_col0\" class=\"data row18 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col1\" class=\"data row18 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col2\" class=\"data row18 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col3\" class=\"data row18 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col4\" class=\"data row18 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col5\" class=\"data row18 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col6\" class=\"data row18 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col7\" class=\"data row18 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col8\" class=\"data row18 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col9\" class=\"data row18 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col10\" class=\"data row18 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col11\" class=\"data row18 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row18_col12\" class=\"data row18 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row19\" class=\"row_heading level0 row19\" >T</th>\n",
       "      <td id=\"T_6cdde_row19_col0\" class=\"data row19 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col1\" class=\"data row19 col1\" >1.58%</td>\n",
       "      <td id=\"T_6cdde_row19_col2\" class=\"data row19 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col3\" class=\"data row19 col3\" >0.16%</td>\n",
       "      <td id=\"T_6cdde_row19_col4\" class=\"data row19 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col5\" class=\"data row19 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col6\" class=\"data row19 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col7\" class=\"data row19 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col8\" class=\"data row19 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col9\" class=\"data row19 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col10\" class=\"data row19 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row19_col11\" class=\"data row19 col11\" >1.61%</td>\n",
       "      <td id=\"T_6cdde_row19_col12\" class=\"data row19 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row20\" class=\"row_heading level0 row20\" >TGT</th>\n",
       "      <td id=\"T_6cdde_row20_col0\" class=\"data row20 col0\" >6.02%</td>\n",
       "      <td id=\"T_6cdde_row20_col1\" class=\"data row20 col1\" >4.56%</td>\n",
       "      <td id=\"T_6cdde_row20_col2\" class=\"data row20 col2\" >7.40%</td>\n",
       "      <td id=\"T_6cdde_row20_col3\" class=\"data row20 col3\" >4.97%</td>\n",
       "      <td id=\"T_6cdde_row20_col4\" class=\"data row20 col4\" >7.70%</td>\n",
       "      <td id=\"T_6cdde_row20_col5\" class=\"data row20 col5\" >8.05%</td>\n",
       "      <td id=\"T_6cdde_row20_col6\" class=\"data row20 col6\" >13.12%</td>\n",
       "      <td id=\"T_6cdde_row20_col7\" class=\"data row20 col7\" >16.65%</td>\n",
       "      <td id=\"T_6cdde_row20_col8\" class=\"data row20 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row20_col9\" class=\"data row20 col9\" >3.67%</td>\n",
       "      <td id=\"T_6cdde_row20_col10\" class=\"data row20 col10\" >0.22%</td>\n",
       "      <td id=\"T_6cdde_row20_col11\" class=\"data row20 col11\" >2.60%</td>\n",
       "      <td id=\"T_6cdde_row20_col12\" class=\"data row20 col12\" >2.84%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row21\" class=\"row_heading level0 row21\" >TMO</th>\n",
       "      <td id=\"T_6cdde_row21_col0\" class=\"data row21 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col1\" class=\"data row21 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col2\" class=\"data row21 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col3\" class=\"data row21 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col4\" class=\"data row21 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col5\" class=\"data row21 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col6\" class=\"data row21 col6\" >0.01%</td>\n",
       "      <td id=\"T_6cdde_row21_col7\" class=\"data row21 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col8\" class=\"data row21 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col9\" class=\"data row21 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col10\" class=\"data row21 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col11\" class=\"data row21 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row21_col12\" class=\"data row21 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row22\" class=\"row_heading level0 row22\" >TXT</th>\n",
       "      <td id=\"T_6cdde_row22_col0\" class=\"data row22 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col1\" class=\"data row22 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col2\" class=\"data row22 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col3\" class=\"data row22 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col4\" class=\"data row22 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col5\" class=\"data row22 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col6\" class=\"data row22 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col7\" class=\"data row22 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col8\" class=\"data row22 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col9\" class=\"data row22 col9\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col10\" class=\"data row22 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col11\" class=\"data row22 col11\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row22_col12\" class=\"data row22 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row23\" class=\"row_heading level0 row23\" >VZ</th>\n",
       "      <td id=\"T_6cdde_row23_col0\" class=\"data row23 col0\" >11.37%</td>\n",
       "      <td id=\"T_6cdde_row23_col1\" class=\"data row23 col1\" >11.46%</td>\n",
       "      <td id=\"T_6cdde_row23_col2\" class=\"data row23 col2\" >10.48%</td>\n",
       "      <td id=\"T_6cdde_row23_col3\" class=\"data row23 col3\" >12.54%</td>\n",
       "      <td id=\"T_6cdde_row23_col4\" class=\"data row23 col4\" >10.28%</td>\n",
       "      <td id=\"T_6cdde_row23_col5\" class=\"data row23 col5\" >12.48%</td>\n",
       "      <td id=\"T_6cdde_row23_col6\" class=\"data row23 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row23_col7\" class=\"data row23 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row23_col8\" class=\"data row23 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row23_col9\" class=\"data row23 col9\" >3.68%</td>\n",
       "      <td id=\"T_6cdde_row23_col10\" class=\"data row23 col10\" >8.05%</td>\n",
       "      <td id=\"T_6cdde_row23_col11\" class=\"data row23 col11\" >5.08%</td>\n",
       "      <td id=\"T_6cdde_row23_col12\" class=\"data row23 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6cdde_level0_row24\" class=\"row_heading level0 row24\" >ZION</th>\n",
       "      <td id=\"T_6cdde_row24_col0\" class=\"data row24 col0\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col1\" class=\"data row24 col1\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col2\" class=\"data row24 col2\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col3\" class=\"data row24 col3\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col4\" class=\"data row24 col4\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col5\" class=\"data row24 col5\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col6\" class=\"data row24 col6\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col7\" class=\"data row24 col7\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col8\" class=\"data row24 col8\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col9\" class=\"data row24 col9\" >6.84%</td>\n",
       "      <td id=\"T_6cdde_row24_col10\" class=\"data row24 col10\" >0.00%</td>\n",
       "      <td id=\"T_6cdde_row24_col11\" class=\"data row24 col11\" >3.04%</td>\n",
       "      <td id=\"T_6cdde_row24_col12\" class=\"data row24 col12\" >0.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x301e44710>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_s.style.format(\"{:.2%}\").background_gradient(cmap='YlGn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plotting a comparison of assets weights for each portfolio\n",
    "\n",
    "fig = plt.gcf()\n",
    "fig.set_figwidth(14)\n",
    "fig.set_figheight(6)\n",
    "ax = fig.subplots(nrows=1, ncols=1)\n",
    "\n",
    "w_s.plot.bar(ax=ax)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "vscode": {
   "interpreter": {
    "hash": "6e72041bc49a6ff39e74ccd56b9391c544b799a0d2a04160b530f8b1ce965df8"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
